###### Statistics, Nonparametric

A class of statistical methods applicable to a large set of probability distributions used to test for correlation, location, independence, etc. In most nonparametric statistical tests, the original scores or observations are replaced by another variable containing less information. An important class of nonparametric tests employs the ordinal properties of the data. Another class of tests uses information about whether an observation is above or below some fixed value such as the median, and a third class is based on the frequency of the occurrence of runs in the data. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed, p1284; Corsini, Concise Encyclopedia of Psychology, 1987, p764-5)

###### Models, Statistical

###### Genetic Linkage

###### Lod Score

###### Data Interpretation, Statistical

###### Statistics as Topic

###### Computer Simulation

###### Biometry

###### Models, Genetic

###### Algorithms

###### Chromosome Mapping

###### Bayes Theorem

A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.

###### Genetic Markers

###### Likelihood Functions

###### Pedigree

###### Reproducibility of Results

The statistical reproducibility of measurements (often in a clinical context), including the testing of instrumentation or techniques to obtain reproducible results. The concept includes reproducibility of physiological measurements, which may be used to develop rules to assess probability or prognosis, or response to a stimulus; reproducibility of occurrence of a condition; and reproducibility of experimental results.

###### Chromosomes, Human, Pair 1

###### Monte Carlo Method

In statistics, a technique for numerically approximating the solution of a mathematical problem by studying the distribution of some random variable, often generated by a computer. The name alludes to the randomness characteristic of the games of chance played at the gambling casinos in Monte Carlo. (From Random House Unabridged Dictionary, 2d ed, 1993)

###### Genetic Heterogeneity

The presence of apparently similar characters for which the genetic evidence indicates that different genes or different genetic mechanisms are involved in different pedigrees. In clinical settings genetic heterogeneity refers to the presence of a variety of genetic defects which cause the same disease, often due to mutations at different loci on the same gene, a finding common to many human diseases including ALZHEIMER DISEASE; CYSTIC FIBROSIS; LIPOPROTEIN LIPASE DEFICIENCY, FAMILIAL; and POLYCYSTIC KIDNEY DISEASES. (Rieger, et al., Glossary of Genetics: Classical and Molecular, 5th ed; Segen, Dictionary of Modern Medicine, 1992)

###### Genome, Human

###### Sample Size

###### Microsatellite Repeats

###### Genetic Predisposition to Disease

###### Matched-Pair Analysis

###### Biostatistics

###### Software

###### National Center for Health Statistics (U.S.)

###### Regression Analysis

Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.

###### Sensitivity and Specificity

###### Chromosomes, Human, Pair 2

###### Genotype

###### Quantitative Trait, Heritable

###### ROC Curve

###### Chromosomes, Human, Pair 6

###### Family Health

###### Chromosomes, Human, Pair 7

###### Chromosomes, Human, Pair 10

###### Genetic Diseases, Inborn

###### Siblings

###### Decision Theory

###### Markov Chains

###### Confidence Intervals

###### Bias (Epidemiology)

Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.

###### Chromosomes, Human, Pair 4

###### Penetrance

###### Normal Distribution

###### Genes, Dominant

###### Chromosomes, Human, Pair 12

###### Oligonucleotide Array Sequence Analysis

###### Models, Biological

###### Analysis of Variance

###### Research Design

###### Haplotypes

###### Reference Values

###### Gene Expression Profiling

###### Chromosomes, Human, Pair 3

###### Image Interpretation, Computer-Assisted

###### Alleles

###### Linear Models

###### Models, Theoretical

###### Age Factors

Age as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or the effect of a circumstance. It is used with human or animal concepts but should be differentiated from AGING, a physiological process, and TIME FACTORS which refers only to the passage of time.

###### Cluster Analysis

A set of statistical methods used to group variables or observations into strongly inter-related subgroups. In epidemiology, it may be used to analyze a closely grouped series of events or cases of disease or other health-related phenomenon with well-defined distribution patterns in relation to time or place or both.

###### Linkage Disequilibrium

###### Case-Control Studies

Studies which start with the identification of persons with a disease of interest and a control (comparison, referent) group without the disease. The relationship of an attribute to the disease is examined by comparing diseased and non-diseased persons with regard to the frequency or levels of the attribute in each group.

###### Epistasis, Genetic

A form of gene interaction whereby the expression of one gene interferes with or masks the expression of a different gene or genes. Genes whose expression interferes with or masks the effects of other genes are said to be epistatic to the effected genes. Genes whose expression is affected (blocked or masked) are hypostatic to the interfering genes.

###### Genome-Wide Association Study

###### Phenotype

###### Longitudinal Studies

###### Pattern Recognition, Automated

###### Cohort Studies

Studies in which subsets of a defined population are identified. These groups may or may not be exposed to factors hypothesized to influence the probability of the occurrence of a particular disease or other outcome. Cohorts are defined populations which, as a whole, are followed in an attempt to determine distinguishing subgroup characteristics.

###### False Positive Reactions

###### Age of Onset

###### Predictive Value of Tests

In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.

###### Image Enhancement

###### Retrospective Studies

Studies used to test etiologic hypotheses in which inferences about an exposure to putative causal factors are derived from data relating to characteristics of persons under study or to events or experiences in their past. The essential feature is that some of the persons under study have the disease or outcome of interest and their characteristics are compared with those of unaffected persons.

###### Risk Factors

###### Nonlinear Dynamics

The study of systems which respond disproportionately (nonlinearly) to initial conditions or perturbing stimuli. Nonlinear systems may exhibit "chaos" which is classically characterized as sensitive dependence on initial conditions. Chaotic systems, while distinguished from more ordered periodic systems, are not random. When their behavior over time is appropriately displayed (in "phase space"), constraints are evident which are described by "strange attractors". Phase space representations of chaotic systems, or strange attractors, usually reveal fractal (FRACTALS) self-similarity across time scales. Natural, including biological, systems often display nonlinear dynamics and chaos.

###### Risk Assessment

###### Questionnaires

###### Polymorphism, Single Nucleotide

###### Image Processing, Computer-Assisted

###### Computational Biology

A field of biology concerned with the development of techniques for the collection and manipulation of biological data, and the use of such data to make biological discoveries or predictions. This field encompasses all computational methods and theories for solving biological problems including manipulation of models and datasets.

###### Multivariate Analysis

###### Cross-Sectional Studies

###### Sex Factors

Maleness or femaleness as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or effect of a circumstance. It is used with human or animal concepts but should be differentiated from SEX CHARACTERISTICS, anatomical or physiological manifestations of sex, and from SEX DISTRIBUTION, the number of males and females in given circumstances.

###### Prospective Studies

###### Logistic Models

Statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. A common application is in epidemiology for estimating an individual's risk (probability of a disease) as a function of a given risk factor.

###### Quality Control

###### Genome

###### Survival Analysis

A class of statistical procedures for estimating the survival function (function of time, starting with a population 100% well at a given time and providing the percentage of the population still well at later times). The survival analysis is then used for making inferences about the effects of treatments, prognostic factors, exposures, and other covariates on the function.

###### Chromosomes, Human, Pair 18

###### Principal Component Analysis

###### Treatment Outcome

###### Area Under Curve

A statistical means of summarizing information from a series of measurements on one individual. It is frequently used in clinical pharmacology where the AUC from serum levels can be interpreted as the total uptake of whatever has been administered. As a plot of the concentration of a drug against time, after a single dose of medicine, producing a standard shape curve, it is a means of comparing the bioavailability of the same drug made by different companies. (From Winslade, Dictionary of Clinical Research, 1992)

###### Pregnancy

###### European Continental Ancestry Group

###### Databases, Factual

Extensive collections, reputedly complete, of facts and data garnered from material of a specialized subject area and made available for analysis and application. The collection can be automated by various contemporary methods for retrieval. The concept should be differentiated from DATABASES, BIBLIOGRAPHIC which is restricted to collections of bibliographic references.

###### Chromosomes, Human

###### Chromosomes, Human, Pair 16

###### Chromosomes, Human, Pair 17

###### Chromosomes, Human, Pair 5

###### Chromosomes, Human, Pair 15

###### Genetic Testing

###### Chromosomes, Human, Pair 9

###### Genetics, Population

###### Chromosomes, Human, Pair 20

###### Randomized Controlled Trials as Topic

###### Artificial Intelligence

###### Epidemiologic Methods

###### Magnetic Resonance Imaging

###### Imaging, Three-Dimensional

The process of generating three-dimensional images by electronic, photographic, or other methods. For example, three-dimensional images can be generated by assembling multiple tomographic images with the aid of a computer, while photographic 3-D images (HOLOGRAPHY) can be made by exposing film to the interference pattern created when two laser light sources shine on an object.

###### Biological Markers

Measurable and quantifiable biological parameters (e.g., specific enzyme concentration, specific hormone concentration, specific gene phenotype distribution in a population, presence of biological substances) which serve as indices for health- and physiology-related assessments, such as disease risk, psychiatric disorders, environmental exposure and its effects, disease diagnosis, metabolic processes, substance abuse, pregnancy, cell line development, epidemiologic studies, etc.

###### Death Certificates

###### Breeding

###### Brain

The part of CENTRAL NERVOUS SYSTEM that is contained within the skull (CRANIUM). Arising from the NEURAL TUBE, the embryonic brain is comprised of three major parts including PROSENCEPHALON (the forebrain); MESENCEPHALON (the midbrain); and RHOMBENCEPHALON (the hindbrain). The developed brain consists of CEREBRUM; CEREBELLUM; and other structures in the BRAIN STEM.

###### Gene Frequency

###### Incidence

###### Genetic Loci

Specific regions that are mapped within a GENOME. Genetic loci are usually identified with a shorthand notation that indicates the chromosome number and the position of a specific band along the P or Q arm of the chromosome where they are found. For example the locus 6p21 is found within band 21 of the P-arm of CHROMOSOME 6. Many well known genetic loci are also known by common names that are associated with a genetic function or HEREDITARY DISEASE.

###### Clinical Trials as Topic

Works about pre-planned studies of the safety, efficacy, or optimum dosage schedule (if appropriate) of one or more diagnostic, therapeutic, or prophylactic drugs, devices, or techniques selected according to predetermined criteria of eligibility and observed for predefined evidence of favorable and unfavorable effects. This concept includes clinical trials conducted both in the U.S. and in other countries.

###### Chromosomes, Human, Pair 11

###### Follow-Up Studies

###### Chromosomes, Human, Pair 19

###### Chi-Square Distribution

A distribution in which a variable is distributed like the sum of the squares of any given independent random variable, each of which has a normal distribution with mean of zero and variance of one. The chi-square test is a statistical test based on comparison of a test statistic to a chi-square distribution. The oldest of these tests are used to detect whether two or more population distributions differ from one another.

###### Neoplasms

###### Proportional Hazards Models

###### Nephelometry and Turbidimetry

Chemical analysis based on the phenomenon whereby light, passing through a medium with dispersed particles of a different refractive index from that of the medium, is attenuated in intensity by scattering. In turbidimetry, the intensity of light transmitted through the medium, the unscattered light, is measured. In nephelometry, the intensity of the scattered light is measured, usually, but not necessarily, at right angles to the incident light beam.

###### Space-Time Clustering

###### Physical Chromosome Mapping

Mapping of the linear order of genes on a chromosome with units indicating their distances by using methods other than genetic recombination. These methods include nucleotide sequencing, overlapping deletions in polytene chromosomes, and electron micrography of heteroduplex DNA. (From King & Stansfield, A Dictionary of Genetics, 5th ed)

###### Observer Variation

The failure by the observer to measure or identify a phenomenon accurately, which results in an error. Sources for this may be due to the observer's missing an abnormality, or to faulty technique resulting in incorrect test measurement, or to misinterpretation of the data. Two varieties are inter-observer variation (the amount observers vary from one another when reporting on the same material) and intra-observer variation (the amount one observer varies between observations when reporting more than once on the same material).

###### Prevalence

###### Severity of Illness Index

###### Prognosis

###### Statistical Distributions

The complete summaries of the frequencies of the values or categories of a measurement made on a group of items, a population, or other collection of data. The distribution tells either how many or what proportion of the group was found to have each value (or each range of values) out of all the possible values that the quantitative measure can have.

###### Diabetes Mellitus, Type 2

A subclass of DIABETES MELLITUS that is not INSULIN-responsive or dependent (NIDDM). It is characterized initially by INSULIN RESISTANCE and HYPERINSULINEMIA; and eventually by GLUCOSE INTOLERANCE; HYPERGLYCEMIA; and overt diabetes. Type II diabetes mellitus is no longer considered a disease exclusively found in adults. Patients seldom develop KETOSIS but often exhibit OBESITY.

###### Chromosomes, Human, Pair 13

###### Sequence Analysis, DNA

###### Gestational Age

###### Pilot Projects

###### Random Allocation

###### Cause of Death

###### Bipolar Disorder

###### Evolution, Molecular

###### Data Collection

###### Body Mass Index

An indicator of body density as determined by the relationship of BODY WEIGHT to BODY HEIGHT. BMI=weight (kg)/height squared (m2). BMI correlates with body fat (ADIPOSE TISSUE). Their relationship varies with age and gender. For adults, BMI falls into these categories: below 18.5 (underweight); 18.5-24.9 (normal); 25.0-29.9 (overweight); 30.0 and above (obese). (National Center for Health Statistics, Centers for Disease Control and Prevention)

###### Schizophrenia

###### HIV Infections

###### Alcoholism

A primary, chronic disease with genetic, psychosocial, and environmental factors influencing its development and manifestations. The disease is often progressive and fatal. It is characterized by impaired control over drinking, preoccupation with the drug alcohol, use of alcohol despite adverse consequences, and distortions in thinking, most notably denial. Each of these symptoms may be continuous or periodic. (Morse & Flavin for the Joint Commission of the National Council on Alcoholism and Drug Dependence and the American Society of Addiction Medicine to Study the Definition and Criteria for the Diagnosis of Alcoholism: in JAMA 1992;268:1012-4)

###### Age Distribution

###### Poisson Distribution

###### Quality of Life

###### Registries

###### Population Surveillance

###### Sex Distribution

###### Canada

###### Tumor Markers, Biological

Molecular products metabolized and secreted by neoplastic tissue and characterized biochemically in cells or body fluids. They are indicators of tumor stage and grade as well as useful for monitoring responses to treatment and predicting recurrence. Many chemical groups are represented including hormones, antigens, amino and nucleic acids, enzymes, polyamines, and specific cell membrane proteins and lipids.

###### Brain Neoplasms

Neoplasms of the intracranial components of the central nervous system, including the cerebral hemispheres, basal ganglia, hypothalamus, thalamus, brain stem, and cerebellum. Brain neoplasms are subdivided into primary (originating from brain tissue) and secondary (i.e., metastatic) forms. Primary neoplasms are subdivided into benign and malignant forms. In general, brain tumors may also be classified by age of onset, histologic type, or presenting location in the brain.

###### Demography

###### Obesity

A status with BODY WEIGHT that is grossly above the acceptable or desirable weight, usually due to accumulation of excess FATS in the body. The standards may vary with age, sex, genetic or cultural background. In the BODY MASS INDEX, a BMI greater than 30.0 kg/m2 is considered obese, and a BMI greater than 40.0 kg/m2 is considered morbidly obese (MORBID OBESITY).

###### Double-Blind Method

###### Socioeconomic Factors

###### Wounds and Injuries

###### Lupus Erythematosus, Systemic

A chronic, relapsing, inflammatory, and often febrile multisystemic disorder of connective tissue, characterized principally by involvement of the skin, joints, kidneys, and serosal membranes. It is of unknown etiology, but is thought to represent a failure of the regulatory mechanisms of the autoimmune system. The disease is marked by a wide range of system dysfunctions, an elevated erythrocyte sedimentation rate, and the formation of LE cells in the blood or bone marrow.

###### Mutation

###### Health Surveys

###### Geographic Information Systems

###### Poisoning

###### Birth Certificates

###### Life Expectancy

###### Infant Mortality

###### International Classification of Diseases

A system of categories to which morbid entries are assigned according to established criteria. Included is the entire range of conditions in a manageable number of categories, grouped to facilitate mortality reporting. It is produced by the World Health Organization (From ICD-10, p1). The Clinical Modifications, produced by the UNITED STATES DEPT. OF HEALTH AND HUMAN SERVICES, are larger extensions used for morbidity and general epidemiological purposes, primarily in the U.S.

###### Nature

###### Geography

###### Dose-Response Relationship, Drug

###### Diffusion Tensor Imaging

###### Anisotropy

A physical property showing different values in relation to the direction in or along which the measurement is made. The physical property may be with regard to thermal or electric conductivity or light refraction. In crystallography, it describes crystals whose index of refraction varies with the direction of the incident light. It is also called acolotropy and colotropy. The opposite of anisotropy is isotropy wherein the same values characterize the object when measured along axes in all directions.

## Reconstruction of the anterior cruciate ligament: comparison of outside-in and all-inside techniques. (1/11504)

The aim of this prospective study was to compare two arthroscopic techniques for reconstructing the anterior cruciate ligament, the "outside-in" (two incisions) and the "all-inside" (one incision) techniques. The results obtained for 30 patients operated on using the "outside-in" technique (group I) were compared with those for 29 patients operated on using the "all-inside" technique (group II). Before surgery, there were no significant differences between the groups in terms of Lysholm score, Tegner activity level, patellofemoral pain score, or knee laxity. Both groups displayed significant improvements in Lysholm score after 24 months, from 69 (16) to 91 (9) in group I and from 70 (17) to 90 (15) in group II (means (SD)). There were also significant improvements in patellofemoral pain scores in both groups, from 13 (6) to 18 (5) in group I and from 14 (6) to 18 (4) in group II after 24 months. No difference was found between the groups in knee stability at the 24 month follow up. The IKDC score was identical in both groups at follow up. The operation took significantly longer for patients in group I (mean 94 (15)) than for those in group II (mean 86 (20)) (p = 0.03). The mean sick leave was 7.7 (6.2) weeks in group I and 12.3 (9.7) weeks in group II (p = 0.026), indicating that there may be a higher morbidity associated with the "all-inside" technique. It can be concluded that there were no significant differences between the two different techniques in terms of functional results, knee laxity, or postoperative complications. The results were satisfactory and the outcome was similar in both treatment groups. (+info)## Statistical inference by confidence intervals: issues of interpretation and utilization. (2/11504)

This article examines the role of the confidence interval (CI) in statistical inference and its advantages over conventional hypothesis testing, particularly when data are applied in the context of clinical practice. A CI provides a range of population values with which a sample statistic is consistent at a given level of confidence (usually 95%). Conventional hypothesis testing serves to either reject or retain a null hypothesis. A CI, while also functioning as a hypothesis test, provides additional information on the variability of an observed sample statistic (ie, its precision) and on its probable relationship to the value of this statistic in the population from which the sample was drawn (ie, its accuracy). Thus, the CI focuses attention on the magnitude and the probability of a treatment or other effect. It thereby assists in determining the clinical usefulness and importance of, as well as the statistical significance of, findings. The CI is appropriate for both parametric and nonparametric analyses and for both individual studies and aggregated data in meta-analyses. It is recommended that, when inferential statistical analysis is performed, CIs should accompany point estimates and conventional hypothesis tests wherever possible. (+info)## Comparison of in vivo and in vitro tests of resistance in patients treated with chloroquine in Yaounde, Cameroon. (3/11504)

The usefulness of an isotopic in vitro assay in the field was evaluated by comparing its results with the therapeutic response determined by the simplified WHO in vivo test in symptomatic Cameroonian patients treated with chloroquine. Of the 117 enrolled patients, 102 (87%) completed the 14-day follow-up, and 95 isolates obtained from these patients (46 children, 49 adults) yielded an interpretable in vitro test. A total of 57 of 95 patients (60%; 28 children and 29 adults) had an adequate clinical response with negative smears (n = 46) or with an asymptomatic parasitaemia (n = 11) on day 7 and/or day 14. The geometric mean 50% inhibitory concentration of the isolates obtained from these patients was 63.3 nmol/l. Late and early treatment failure was observed in 29 (30.5%) and 9 (9.5%) patients, respectively. The geometric mean 50% inhibitory concentrations of the corresponding isolates were 173 nmol/l and 302 nmol/l. Among the patients responding with late and early treatment failure, five isolates and one isolate, respectively, yielded a discordant result (in vivo resistance and in vitro sensitivity). The sensitivity, specificity, and predictive value of the in vitro test to detect chloroquine-sensitive cases was 67%, 84% and 86%, respectively. There was moderate concordance between the in vitro and in vivo tests (kappa value = 0.48). The in vitro assay agrees relatively well with the therapeutic response and excludes several host factors that influence the results of the in vivo test. However, in view of some discordant results, the in vitro test cannot substitute for in vivo data on therapeutic efficacy. The only reliable definition of "resistance" in malaria parasites is based on clinical and parasitological response in symptomatic patients, and the in vivo test provides the standard method to determine drug sensitivity or resistance as well as to guide national drug policies. (+info)## Elevated hepatic lipase activity and low levels of high density lipoprotein in a normotriglyceridemic, nonobese Turkish population. (4/11504)

Low levels of high density lipoprotein cholesterol (HDL-C) are associated with increased risk of coronary heart disease and, in the United States, are often associated with hypertriglyceridemia and obesity. In Turkey, low HDL-C levels are highly prevalent, 53% of men and 26% of women having HDL-C levels <35 mg/dl, in the absence of hypertriglyceridemia and obesity. In this study to investigate the cause of low HDL-C levels in Turks, various factors affecting HDL metabolism were assessed in normotriglyceridemic Turkish men and women living in Istanbul and in non-Turkish men and women living in San Francisco. Turkish men and women had significantly lower HDL-C levels than the San Francisco men and women, as well as markedly lower apolipoprotein A-I levels (25 and 39 mg/dl lower, respectively). In both Turkish and non-Turkish subjects, the mean body mass index was <27 kg/m2, the mean triglyceride level was <120 mg/dl, and the mean total cholesterol was 170-180 mg/dl. The mean hepatic triglyceride lipase activity was 21% and 31% higher in Turkish men and women, respectively, than in non-Turkish men and women, and remained higher even after subjects with a body mass index >50th percentile for men and women in the United States were excluded from the analysis. As no dietary or behavioral factors have been identified in the Turkish population that account for increased hepatic triglyceride lipase activity, the elevation most likely has a genetic basis. high density lipoprotein in a normotriglyceridemic, nonobese Turkish population. (+info)## Results of three to 10 year follow up of balloon dilatation of the pulmonary valve. (5/11504)

BACKGROUND: The results of immediate and short term follow up of balloon dilatation of the pulmonary valve have been well documented, but there is limited information on long term follow up. OBJECTIVE: To evaluate the results of three to 10 year follow up of balloon dilatation of the pulmonary valve in children and adolescents. SETTING: Tertiary care centre/university hospital. DESIGN: Retrospective study. METHODS AND RESULTS: 85 patients (aged between 1 day and 20 years, mean (SD) 7.0 (6.4) years) underwent balloon dilatation of the pulmonary valve during an 11 year period ending August 1994. There was a resultant reduction in the peak to peak gradient from 87 (38) to 26 (22) mm Hg. Immediate surgical intervention was not required. Residual gradients of 29 (17) mm Hg were measured by catheterisation (n = 47) and echo Doppler (n = 82) at intermediate term follow up (two years). When individual results were scrutinised, nine of 82 patients had restenosis, defined as a peak gradient of 50 mm Hg or more. Seven of these patients underwent repeat balloon dilatation of the pulmonary valve: peak gradients were reduced from 89 (40) to 38 (20) mm Hg. Clinical evaluation and echo Doppler data of 80 patients showed that residual peak instantaneous Doppler gradients were 17 (15) mm Hg at long term follow up (three to 10 years, median seven), with evidence for late restenosis in one patient (1.3%). Surgical intervention was necessary to relieve fixed infundibular stenosis in three patients and supravalvar pulmonary stenosis in one. Repeat balloon dilatation was performed to relieve restenosis in two patients. Actuarial reintervention free rates at one, two, five, and 10 years were 94%, 89%, 88%, and 84%, respectively. Pulmonary valve regurgitation was noted in 70 of 80 patients at late follow up, but neither right ventricular dilatation nor paradoxical interventricular septal motion developed. CONCLUSIONS: The results of late follow up of balloon dilatation of the pulmonary valve are excellent. Repeat balloon dilatation was performed in 11% of patients and surgical intervention for subvalvlar or supravalvar stenosis in 5%. Most patients had mild residual pulmonary regurgitation but right ventricular volume overload was not required. Balloon dilatation is the treatment of choice in the management of moderate to severe stenosis of the pulmonary valve. Further follow up studies should be undertaken to evaluate the significance of residual pulmonary regurgitation. (+info)## Cyclical etidronate increases bone density in the spine and hip of postmenopausal women receiving long term corticosteroid treatment. A double blind, randomised placebo controlled study. (6/11504)

OBJECTIVE: To study the effect of cyclic etidronate in secondary prevention of corticosteroid induced osteoporosis. METHODS: A double blind, randomised placebo controlled study comparing cyclic etidronate and placebo during two years in 37 postmenopausal women receiving long term corticosteroid treatment, mainly for polymyalgia rheumatica (40% of the patients) and rheumatoid arthritis (30%). Bone density was measured in the lumbar spine, femoral neck, and femoral trochanter. RESULTS: After two years of treatment there was a significant difference between the groups in mean per cent change from baseline in bone density in the spine in favour of etidronate (p = 0.003). The estimated treatment difference (mean (SD)) was 9.3 (2.1)%. Etidronate increased bone density in the spine (4.9 (2.1)%, p < 0.05) whereas the placebo group lost bone (-2.4 (1.6)%). At the femoral neck there was an estimated difference of 5.3 (2.6)% between the groups (etidronate: 3.6% (1.4)%, p < 0.05, placebo: -2.4 (2.1)%). The estimated difference at the trochanter was 8.2 (3.0) (etidronate: 9.0 (1.5)%, p < 0.0001, placebo: 0.5 (2.3)%). No significant bone loss occurred in the hip in placebo treated patients. CONCLUSIONS: Cyclic etidronate is an effective treatment for postmenopausal women receiving corticosteroid treatment and is well tolerated. (+info)## Progression from colorectal adenoma to carcinoma is associated with non-random chromosomal gains as detected by comparative genomic hybridisation. (7/11504)

AIMS: Chromosomal gains and losses were surveyed by comparative genomic hybridisation (CGH) in a series of colorectal adenomas and carcinomas, in search of high risk genomic changes involved in colorectal carcinogenesis. METHODS: Nine colorectal adenomas and 14 carcinomas were analysed by CGH, and DNA ploidy was assessed with both flow and image cytometry. RESULTS: In the nine adenomas analysed, an average of 6.6 (range 1 to 11) chromosomal aberrations were identified. In the 14 carcinomas an average of 11.9 (range 5 to 17) events were found per tumour. In the adenomas the number of gains and losses was in balance (3.6 v 3.0) while in carcinomas gains occurred more often than losses (8.2 v 3.7). Frequent gains involved 13q, 7p, 8q, and 20q, whereas losses most often occurred at 18q, 4q, and 8p. Gains of 13q, 8q, and 20q, and loss of 18q occurred more often in carcinomas than in adenomas (p = 0.005, p = 0.05, p = 0.05, and p = 0.02, respectively). Aneuploid tumours showed more gains than losses (mean 9.3 v 4.9, p = 0.02), in contrast to diploid tumours where gains and losses were nearly balanced (mean 3.1 v 4.1, p = 0.5). CONCLUSIONS: The most striking difference between chromosomal aberrations in colorectal adenomas and carcinomas, as detected by CGH, is an increased number of chromosomal gains that show a nonrandom distribution. Gains of 13q and also of 20q and 8q seem especially to be involved in the progression of adenomas to carcinomas, possibly owing to low level overexpression of oncogenes at these loci. (+info)## Effect of 5-HT4 receptor stimulation on the pacemaker current I(f) in human isolated atrial myocytes. (8/11504)

OBJECTIVE: 5-HT4 receptors are present in human atrial cells and their stimulation has been implicated in the genesis of atrial arrhythmias including atrial fibrillation. An I(f)-like current has been recorded in human atrial myocytes, where it is modulated by beta-adrenergic stimulation. In the present study, we investigated the effect of serotonin (5-hydroxytryptamine, 5-HT) on I(f) electrophysiological properties, in order to get an insight into the possible contribution of I(f) to the arrhythmogenic action of 5-HT in human atria. METHODS: Human atrial myocytes were isolated by enzymatic digestion from samples of atrial appendage of patients undergoing coeffective cardiac surgery. Patch-clamped cells were superfused with a modified Tyrode's solution in order to amplify I(f) and reduce overlapping currents. RESULTS AND CONCLUSIONS: A time-dependent, cesium-sensitive increasing inward current, that we had previously described having the electrophysiological properties of the pacemaker current I(f), was elicited by negative steps (-60 to -130 mV) from a holding potential of -40 mV. Boltzmann fit of control activation curves gave a midpoint (V1/2) of -88.9 +/- 2.6 mV (n = 14). 5-HT (1 microM) consistently caused a positive shift of V1/2 of 11.0 +/- 2.0 mV (n = 8, p < 0.001) of the activation curve toward less negative potentials, thus increasing the amount of current activated by clamp steps near the physiological maximum diastolic potential of these cells. The effect was dose-dependent, the EC50 being 0.14 microM. Maximum current amplitude was not changed by 5-HT. 5-HT did not increase I(f) amplitude when the current was maximally activated by cAMP perfused into the cell. The selective 5-HT4 antagonists, DAU 6285 (10 microM) and GR 125487 (1 microM), completely prevented the effect of 5-HT on I(f). The shift of V1/2 caused by 1 microM 5-HT in the presence of DAU 6285 or GR 125487 was 0.3 +/- 1 mV (n = 6) and 1.0 +/- 0.6 mV (n = 5), respectively (p < 0.01 versus 5-HT alone). The effect of 5-HT4 receptor blockade was specific, since neither DAU 6285 nor GR 125487 prevented the effect of 1 microM isoprenaline on I(f). Thus, 5-HT4 stimulation increases I(f) in human atrial myocytes; this effect may contribute to the arrhythmogenic action of 5-HT in human atrium. (+info)###### Nonparametric tests for the pathwise properties of semimartingales

###### Section 8.5 - Section 8.5 A Nonparametric Test The two-sample t-test even for the normal populations may not be the best or the...

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###### Friedman test

1988).

**Nonparametric****Statistics**for the Behavioral Sciences (2nd ed.). New York: McGraw-Hill. ISBN 978-0-07-100326-1.. ... Kendall's W is a normalization of the Friedman**statistic**between 0 and 1. The Wilcoxon signed-rank test is a**nonparametric**test ... ISBN 978-0-85264-199-6. Hollander, M.; Wolfe, D. A. (1973).**Nonparametric****Statistics**. New York: J. Wiley. ISBN 978-0-471-40635- ... ISBN 3-540-13776-9. Conover, W. J. (1971, 1980). Practical**nonparametric****statistics**. New York: Wiley. ISBN 0-471-16851-3. Bortz ...###### Boundary problem (spatial analysis)

Elementary

**statistics**for geographers (3rd ed.). Guilford Press. ISBN 978-1572304840. Henley, S. (1981).**Nonparametric**... Cressie, Noel A. C. (1993).**Statistics**for Spatial Data. Wiley Series in Probability and**Statistics**. Wiley. doi:10.1002/ ... In analysis with area data,**statistics**should be interpreted based upon the boundary. In geographical research, two types of ... In analysis with areal data,**statistics**should be interpreted based upon the boundary. In spatial analysis, four major problems ...###### Lepage test

In

**statistics**, the Lepage test is an exactly distribution-free test (**nonparametric**test) for jointly monitoring the location ( ... The Lepage test**statistic**is the squared Euclidean distance of standardized Wilcoxon rank-sum test for location and the ... Andreas Schulz and Markus Neuhäuser also provided detailed R code for computation of test**statistic**and p-value of the Lepage ... The details may be found in the book:**Nonparametric**statistical tests: A computational approach. Kössler, W. in 2006 also ...###### Sign test

Kitchens, L.J.(2003). Basic

**Statistics**and Data Analysis. Duxbury. Conover, W. J. (1980). Practical**Nonparametric****Statistics**, ... Mendenhall W, Wackerly DD, Scheaffer RL (1989), "15:**Nonparametric****statistics**", Mathematical**statistics**with applications ( ... Practical**Nonparametric****Statistics**(Third ed.), Wiley, pp. 157-176, ISBN 0-471-16068-7 Sprent, P. (1989), Applied**Nonparametric**... Corder, Gregory W.; Foreman, Dale I. (2014), "3.6 Statistical Power",**Nonparametric****Statistics**: A Step-by-Step Approach (2nd ed ...###### Graphon

In graph theory and

**statistics**, a graphon (also known as a graph limit) is a symmetric measurable function W : [ 0 , 1 ] 2 → [ ... Wolfe, Patrick J.; Olhede, Sofia C. (2013-09-23). "**Nonparametric**graphon estimation". arXiv:1309.5936 [math.ST]. Choi, David; ... Gao, Chao; Lu, Yu; Zhou, Harrison H. (December 2015). "Rate-optimal graphon estimation". The Annals of**Statistics**. 43 (6): 2624 ... Wolfe, Patrick J. (February 2014). "Co-clustering separately exchangeable network data". The Annals of**Statistics**. 42 (1): 29- ...###### K-nearest neighbors algorithm

In

**statistics**, the k-nearest neighbors algorithm (k-NN) is a**non-parametric**classification method first developed by Evelyn Fix ... Stone, Charles J. (1977). "Consistent**nonparametric**regression". Annals of**Statistics**. 5 (4): 595-620. doi:10.1214/aos/ ...**Nonparametric**Discrimination: Consistency Properties (PDF) (Report). USAF School of Aviation Medicine, Randolph Field, Texas. ... Terrell, George R.; Scott, David W. (1992). "Variable kernel density estimation". Annals of**Statistics**. 20 (3): 1236-1265. doi: ...###### Hodges-Lehmann estimator

... an important class of estimators both in

**nonparametric****statistics**and in robust**statistics**. The Hodges-Lehmann estimator was ... In**statistics**, the Hodges-Lehmann estimator is a robust and**nonparametric**estimator of a population's location parameter. For ... It is a robust**statistic**that has a breakdown point of 0.29, which means that the**statistic**remains bounded even if nearly 30 ... The Hodges-Lehmann univariate**statistics**have several generalizations in multivariate**statistics**: Multivariate ranks and signs ...###### Wald-Wolfowitz runs test

Alhakim, A; Hooper, W (2008). "A

**non-parametric**test for several independent samples". Journal of**Nonparametric****Statistics**. 20 ... The Wald-Wolfowitz runs test (or simply runs test), named after statisticians Abraham Wald and Jacob Wolfowitz is a**non-parametric**... Sprent P, Smeeton NC (2007) Applied**Nonparametric**Statistical Methods, pp. 217-219. Boca Raton: Chapman & Hall/ CRC. ...###### Page's trend test

Applied

**Nonparametric****Statistics**(2nd ed.). Boston: PWS-Kent. pp. 279-284. ISBN 0-534-91976-6.**Nonparametric**Tests of Trend. ... In**statistics**, the Page test for multiple comparisons between ordered correlated variables is the counterpart of Spearman's ...###### Cucconi test

In

**statistics**, the Cucconi test is a**nonparametric**test for jointly comparing central tendency and variability (detecting ... Journal of**Nonparametric****Statistics**. 21 (5): 629-647. doi:10.1080/10485250902952435. Mukherjee, Amitava; Marozzi, Marco (2017- ... The Cucconi test is based on the following**statistic**: CUC = U 2 + V 2 − 2 ρ U V 2 ( 1 − ρ 2 ) . {\displaystyle {\text{CUC}}={\ ... Marozzi, Marco (2013). "**Nonparametric**Simultaneous Tests for Location and Scale Testing: a Comparison of Several Methods". ...###### Stein's unbiased risk estimate

Wasserman, Larry (2005). All of

**Nonparametric****Statistics**.. ... In**statistics**, Stein's unbiased risk estimate (SURE) is an ... Stein, Charles M. (November 1981). "Estimation of the Mean of a Multivariate Normal Distribution". The Annals of**Statistics**. 9 ...###### Analysis of variance

Robust

**nonparametric**statistical methods. Kendall's Library of**Statistics**. Volume 5 (First ed.). New York: John Wiley & Sons, ... The test**statistics**of this derived linear model are closely approximated by the test**statistics**of an appropriate normal ... Citations from Moore & McCabe (2003): "Analysis of variance uses F**statistics**, but these are not the same as the F**statistic**... Resampling and**nonparametric**approaches to data) Montgomery (2001, Section 3-10:**Nonparametric**methods in the analysis of ...###### Shlomo Sawilowsky

Many of his publications are related to rank-based

**nonparametric****statistics**. For example, an examination of the robustness and ... Hettmansperger, T. P.; McKean, J. W. (1998). Robust**nonparametric**statistical methods. Kendall's Library of**Statistics**. 5 ( ... 1990**Nonparametric**tests of interaction in experimental design. Review of Educational Research, 60, 91-126. 1989 (With R. C. ... Journal of Educational**Statistics**, 14, 255-267. After graduating from the Rabbinical College of America in 1979, Sawilowsky was ...###### Step detection

Winkler, G.; Liebscher, V. (2002). "Smoothers for discontinuous signals". Journal of

**Nonparametric****Statistics**. 14 (1-2): 203- ... In**statistics**and signal processing, step detection (also known as step smoothing, step filtering, shift detection, jump ... 2008). "Complexity penalized M-estimation: fast computation". Journal of Computational and Graphical**Statistics**. 17 (1): 201- ...###### Kolmogorov-Smirnov test

Journal of

**Nonparametric****Statistics**. 21 (5): 629-647. doi:10.1080/10485250902952435. Marozzi, Marco (2013). "**Nonparametric**... R's**statistics**base-package implements the test as ks.test {**stats**} in its "**stats**" package. SAS implements the test in its PROC ... In**statistics**, the Kolmogorov-Smirnov test (K-S test or KS test) is a**nonparametric**test of the equality of continuous (or ... Corder, G. W.; Foreman, D. I. (2014).**Nonparametric****Statistics**: A Step-by-Step Approach. Wiley. ISBN 978-1118840313. Stephens, ...###### Xiaohong Chen

Journal of

**Nonparametric****Statistics**, 22(4), 419-423. Chen, X., & Christensen, T. M. (2015). Optimal Sup-norm Rates and Uniform ... The winner of The Journal of**Nonparametric****Statistics**2010 Best Paper Award In the article, Raymond J. Carroll, Xiaohong Chen ... Journal of**Nonparametric****Statistics**. 22 (4): 379-399. doi:10.1080/10485250902874688. ISSN 1048-5252. PMC 2873792. PMID 20495685 ... China 2012 Econometric Theory Multa Scripsit Award 2010 The winner of The Journal of**Nonparametric****Statistics**2010 Best Paper ...###### Chebyshev's inequality

Kabán, Ata (2012). "

**Non-parametric**detection of meaningless distances in high dimensional data".**Statistics**and Computing. 22 ( ... Hartigan, J. A.; Hartigan, P. M. (1985). "The Dip Test of Unimodality". The Annals of**Statistics**. 13: 70-84. doi:10.1214/aos/ ... C (Applied**Statistics**). 53 (1): 95-108. doi:10.1111/j.1467-9876.2004.00428.x. ISSN 1467-9876. Savage, I. Richard. "Probability ... McWilliams, Thomas P. (1990). "A Distribution-Free Test for Symmetry Based on a Runs**Statistic**". Journal of the American ...###### Larry A. Wasserman

He has also written two advanced

**statistics**textbooks, All of**Statistics**and All of**Nonparametric****Statistics**. 2004. All of ... All of**Nonparametric****Statistics**. New York: Springer, 2006. ISBN 978-0-387-25145-5 Larry Wasserman Elected To National Academy ... All of**Nonparametric****Statistics**. Springer. ISBN 978-0-387-25145-5 2013. Topological Inference. Reitz Lecture 2013. 2016, Member ... All of**Statistics**: A Concise Course in Statistical Inference. New York: Springer, 2004. ISBN 978-0-387-40272-7 Wasserman, Larry ...###### Median

Hettmansperger, Thomas P.; McKean, Joseph W. (1998). Robust

**nonparametric**statistical methods. Kendall's Library of**Statistics**... The median is of central importance in robust**statistics**, as it is the most resistant**statistic**, having a breakdown point of 50 ... Pennsylvania State Department of**Statistics**David J. Sheskin (27 August 2003). Handbook of Parametric and**Nonparametric**... the median is a popular summary**statistic**in descriptive**statistics**. In this context, there are several choices for a measure ...###### Multivariate kernel density estimation

"Remarks on some

**nonparametric**estimates of a density function". Annals of Mathematical**Statistics**. 27 (3): 832-837. doi:10.1214 ... Journal of**Nonparametric****Statistics**. 15: 17-30. doi:10.1080/10485250306039. Wand, M.P.; Jones, M.C. (1994). "Multivariate plug- ... Journal of**Nonparametric****Statistics**. 18 (2): 215-226. doi:10.1080/10485250600712008. Marron, J.S.; Tsybakov, A. (1996). "Visual ... ISBN 978-0-387-94716-7. Silverman, B.W. (1986). Density Estimation for**Statistics**and Data Analysis. Chapman & Hall/CRC. pp. 7- ...###### ANOVA on ranks

Conover, W. J.; Iman, R. L. (1981). "Rank transformations as a bridge between parametric and

**nonparametric****statistics**". ... ANOVA on ranks is a**statistic**designed for situations when the normality assumption has been violated. The F**statistic**is a ... Robust**nonparametric**statistical methods. Kendall's Library of**Statistics**. 5 (First ed.). London: Edward Arnold. pp. xiv+467 pp ... Communications in**Statistics**: Computations and Simulations. B16: 1133-1145. Sawilowsky, S. (1990). "**Nonparametric**tests of ...###### k-nearest neighbors algorithm

Stone C. J. (1977). "Consistent

**nonparametric**regression". Annals of**Statistics**. 5 (4): 595-620. doi:10.1214/aos/1176343886.. ... In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a**non-parametric**method used for classification and ... D. G. Terrell; D. W. Scott (1992). "Variable kernel density estimation". Annals of**Statistics**. 20 (3): 1236-, 1265. doi:10.1214 ... Hall P, Park BU, Samworth RJ (2008). "Choice of neighbor order in nearest-neighbor classification". Annals of**Statistics**. 36 (5 ...###### Kendall rank correlation coefficient

Daniel, Wayne W. (1990). "Kendall's tau". Applied

**Nonparametric****Statistics**(2nd ed.). Boston: PWS-Kent. pp. 365-377. ISBN 978-0 ... R's**statistics**base-package implements the test cor.test(x, y, method = "kendall") in its "**stats**" package (also cor(x, y, ... is a**statistic**used to measure the ordinal association between two measured quantities. A τ test is a**non-parametric**hypothesis ... In**statistics**, the Kendall rank correlation coefficient, commonly referred to as Kendall's τ coefficient (after the Greek ...###### Evelyn Fix

"Evelyn Fix,

**Statistics**: Berkeley". In Memoriam. University of California, Berkeley, Department of**Statistics**. Evelyn Fix at the ...**Nonparametric**Discrimination: Consistency Properties," which defined the nearest neighbor rule, an important method that would ... She was appointed as an assistant professor in 1951 and in 1963 she was promoted to Professor of**Statistics**. She died of a ...**Statistics**became a separate department in 1955. In 1951 Fix and Joseph Hodges, Jr. published their groundbreaking paper " ...###### Durbin test

Practical

**Nonparametric****Statistics**(Third ed.). Wiley. pp. 388-395. ISBN 0-471-16068-7. This article incorporates public domain ... The T2**statistic**has slightly more accurate critical regions, so it is now the preferred**statistic**. The T2**statistic**is the two ... The Durbin test is a**nonparametric**test for balanced incomplete designs that reduces to the Friedman test in the case of a ... In the analysis of designed experiments, the Friedman test is the most common**non-parametric**test for complete block designs. ...###### Jaroslav Hájek

A course in

**nonparametric****statistics**. San Francisco: Holden-Day. Jaroslav Hájek at the Mathematics Genealogy Project v t e v t ... was a Czech mathematician who worked in theoretical and**nonparametric****statistics**. The Hájek-Le Cam convolution theorem is named ...###### Species discovery curve

**Nonparametric**prediction in species sampling. Journal of Agricultural Biological and Environmental

**Statistics**, 9, 253-269. ...

###### Cochran's Q test

Conover, William Jay (1999). Practical

**Nonparametric****Statistics**(Third ed.). Wiley, New York, NY USA. pp. 388-395. ISBN ... The Cochran's Q test**statistic**is T = k ( k − 1 ) ∑ j = 1 k ( X ∙ j − N k ) 2 ∑ i = 1 b X i ∙ ( k − X i ∙ ) {\displaystyle T=k\ ... In**statistics**, in the analysis of two-way randomized block designs where the response variable can take only two possible ... The null hypothesis is rejected if the test**statistic**is in the critical region. If the Cochran test rejects the null ...###### Jonckheere's trend test

Leach, C. (1979). Introduction to

**Statistics**: A**non-parametric**approach for the social sciences. Chichester: John Wiley. Loftus ... Daniel, Wayne W. (1990). "Jonckheere-Terpstra tst for ordered alternatives". Applied**Nonparametric****Statistics**(2nd ed.). Boston ... In**statistics**, the Jonckheere trend test (sometimes called the Jonckheere-Terpstra test) is a test for an ordered alternative ... If there are no ties - or the ties occur within a particular sample (which does not affect the value of the test**statistic**) - ...###### Spearman's rank correlation coefficient

... www.mathworks.com/help/

**stats**/corr.html Corder, G. W. & Foreman, D. I. (2014).**Nonparametric****Statistics**: A Step-by-Step Approach ... R's**statistics**base-package implements the test cor.test(x, y, method = "spearman") in its "**stats**" package (also cor(x, y, ... Daniel, Wayne W. (1990). "Spearman rank correlation coefficient". Applied**Nonparametric****Statistics**(2nd ed.). Boston: PWS-Kent ... In**statistics**, Spearman's rank correlation coefficient or Spearman's ρ, named after Charles Spearman and often denoted by the ...###### Level of measurement

Mosteller, Frederick (1977). Data analysis and regression : a second course in

**statistics**. Reading, Mass: Addison-Wesley Pub. ... Sheskin, David J. (2007). Handbook of Parametric and**Nonparametric**Statistical Procedures (Fourth ed.). Boca Raton (FL): ... Readings in**Statistics**, Ch. 3, (Haber, A., Runyon, R. P., and Badia, P.) Reading, Mass: Addison-Wesley, 1970 ... Michell, J. (1986). "Measurement scales and**statistics**: a clash of paradigms". Psychological Bulletin. 100 (3): 398-407. doi: ...###### Mann-Whitney U test

Related test

**statistics**[edit]. Kendall's tau[edit]. The Mann-Whitney U test is related to a number of other**non-parametric**... MATLAB has ranksum in its**Statistics**Toolbox.. *R's**statistics**base-package implements the test wilcox.test. in its "**stats**" ... ρ**statistic**[edit]. A**statistic**called ρ that is linearly related to U and widely used in studies of categorization ( ... Area-under-curve (AUC)**statistic**for ROC curves[edit]. The U**statistic**is equivalent to the area under the receiver operating ...###### 方差分析 - 维基百科，自由的百科全书

Robust

**nonparametric**statistical methods. Kendall's Library of**Statistics**. Volume 5 First. New York: John Wiley & Sons, Inc. ... The Annals of**Statistics**. 2005, 33: 1-53. doi:10.1214/009053604000001048.. *. Gelman, Andrew. Variance, analysis of. The new ...**Statistics**a power primer. Psychology Bulletin. 1992, 112 (1): 155-159. PMID 19565683. doi:10.1037/0033-2909.112.1.155.. ... Lecture Notes in**Statistics**150. New York: Springer-Verlag. 2000. ISBN 978-0-387-98578-7.. ...###### Isotonic regression

**Nonparametric**Bayesian

**statistics**. *Numerical analysis. Hidden categories: *Wikipedia articles needing context from February ... In

**statistics**, isotonic regression or monotonic regression is the technique of fitting a free-form line to a sequence of ... Shively, T.S., Sager, T.W., Walker, S.G. (2009). "A Bayesian approach to

**non-parametric**monotone function estimation". Journal ...

###### Outline of brain mapping

Resampling (

**statistics**) see section on permutation tests.**Nonparametric**Permutation Tests are used in fMRI. ...###### Epistasis

Kempthorne O (1969). An introduction to genetic

**statistics**. Iowa State University Press.. ... For example, multifactor dimensionality reduction (MDR) was designed specifically for**nonparametric**and model-free detection of ...###### Probability distribution

B. S. Everitt: The Cambridge Dictionary of

**Statistics**, Cambridge University Press, Cambridge (3rd edition, 2006). ISBN 0-521- ...**Nonparametric**anova *1-way (Kruskal-Wallis). *2-way (Friedman). *Ordered alternative (Jonckheere-Terpstra) ... In probability theory and**statistics**, a probability distribution is a mathematical function that provides the probabilities of ... and the science of**statistics**. There is spread or variability in almost any value that can be measured in a population (e.g. ...###### Opinion poll

If the

**statistic**is a percentage, this maximum margin of error can be calculated as the radius of the confidence interval for a ...**Nonparametric**anova *1-way (Kruskal-Wallis). *2-way (Friedman). *Ordered alternative (Jonckheere-Terpstra) ... Lynch, Scott M. Introduction to Bayesian**Statistics**and Estimation for Social Scientists (2007). ... The margin of error is usually defined as the radius of a confidence interval for a particular**statistic**from a survey. One ...###### Chi-squared test

Corder, G. W.; Foreman, D. I. (2014),

**Nonparametric****Statistics**: A Step-by-Step Approach, New York: Wiley, ISBN 978-1118840313. ... "Chi-squared**Statistic**". Practical Cryptography. Retrieved 18 February 2015.. *^ "Using Chi Squared to Crack Codes". IB Maths ... In 1900, Pearson published a paper[1] on the χ2 test which is considered to be one of the foundations of modern**statistics**.[6] ... The test**statistic**T in this instance could be set to be the sum of squares about the sample mean, divided by the nominal value ...###### Random assignment

Asymptotic theory (

**statistics**). References[edit]. *^ a b "Social Research Methods - Knowledge Base - Random Selection & ...**Nonparametric**anova *1-way (Kruskal-Wallis). *2-way (Friedman). *Ordered alternative (Jonckheere-Terpstra) ... Lecture Notes in**Statistics**. 150. New York: Springer-Verlag. ISBN 0-387-98578-6. .. ... both for pretreatment checks on equivalence and the evaluation of post treatment results using inferential**statistics**. More ...###### Student's t-test

The test

**statistic**is Hotelling's two-sample t2: t. 2. =. n. 1. n. 2. n. 1. +. n. 2. (. x. ¯. 1. −. x. ¯. 2. ). ′. S. pooled. − ... When the normality assumption does not hold, a**non-parametric**alternative to the t-test can often have better statistical power ... The test**statistic**is Hotelling's t2: t. 2. =. n. (. x. ¯. −. μ. 0. ). ′. S. −. 1. (. x. ¯. −. μ. 0. ). {\displaystyle t^{2}=n ... The t**statistic**to test whether the means are different can be calculated as follows: t. =. X. ¯. 1. −. X. ¯. 2. s. p. 2. n. {\ ...###### Structural equation modeling

Bartholomew, D. J., and Knott, M. (1999) Latent Variable Models and Factor Analysis Kendall's Library of

**Statistics**, vol. 7, ...**Nonparametric**SEMs permit the estimation of total, direct and indirect effects without making any commitment to the form of the ... "Intelligence Tests". Encyclopedia of Measurement and**Statistics**. 2007. doi:10.4135/9781412952644.n220. ISBN 978-1-4129-1611-0. ... Pearl[12] has extended SEM from linear to**nonparametric**models, and proposed causal and counterfactual interpretations of the ...###### Structural break

The bounds test can also be used.[6][8] For cases 1 and 2, the sup-Wald (i.e., the supremum of a set of Wald

**statistics**), sup- ...**Nonparametric**anova *1-way (Kruskal-Wallis). *2-way (Friedman). *Ordered alternative (Jonckheere-Terpstra) ... In econometrics and**statistics**, a structural break is an unexpected change over time in the parameters of regression models, ... In both the**statistics**and econometrics literature we can find very many of papers related to the detection of changes and ...###### Genetic linkage

**Non-parametric**linkage analysis, in turn, studies the probability of an allele being identical by descent with itself. ... or

**non-parametric**. Parametric linkage analysis is the traditional approach, whereby the probability that a gene important for a ...

###### Design of experiments

... frequentist

**statistics**studies the sampling distribution while Bayesian**statistics**updates a probability distribution on the ...**Nonparametric**anova *1-way (Kruskal-Wallis). *2-way (Friedman). *Ordered alternative (Jonckheere-Terpstra) ... Box, George E.P.; Hunter, William G.; Hunter, J. Stuart (1978).**Statistics**for Experimenters : An Introduction to Design, Data ... Box, George E.P.; Hunter, William G.; Hunter, J. Stuart (2005).**Statistics**for Experimenters : Design, Innovation, and ...###### Blinded experiment

Aviva Petrie; Paul Watson (28 February 2013).

**Statistics**for Veterinary and Animal Science. Wiley. pp. 130-131. ISBN 978-1-118- ...**Nonparametric**anova *1-way (Kruskal-Wallis). *2-way (Friedman). *Ordered alternative (Jonckheere-Terpstra) ...###### Analysis of variance

Howell (2002, Chapter 18: Resampling and

**nonparametric**approaches to data) *^ Montgomery (2001, Section 3-10:**Nonparametric**... Citations from Moore & McCabe (2003): "Analysis of variance uses F**statistics**, but these are not the same as the F**statistic**... Biomedical**Statistics**Archived 7 November 2014 at the Wayback Machine *^ "The Probable Error of a Mean" (PDF). Biometrika. 6: 1 ... The test**statistics**of this derived linear model are closely approximated by the test**statistics**of an appropriate normal ...###### k-means clustering

International Conference on Artificial Intelligence and

**Statistics**(AISTATS). Archived from the original (PDF) on 2013-05-10.. ... K-means is closely related to**nonparametric**Bayesian modeling.[38] ... Proceedings of 5th Berkeley Symposium on Mathematical**Statistics**and Probability. 1. University of California Press. pp. 281-, ...**Statistics**

**Nonparametric**anova *1-way (Kruskal-Wallis). *2-way (Friedman). *Ordered alternative (Jonckheere-Terpstra) ... Applied

**statistics**, theoretical

**statistics**and mathematical

**statistics**[edit]. Applied

**statistics**comprises descriptive ... Descriptive

**statistics**is distinguished from inferential

**statistics**(or inductive

**statistics**), in that descriptive

**statistics**... 4.1 Descriptive

**statistics**. *4.2 Inferential

**statistics***4.2.1 Terminology and theory of inferential

**statistics***4.2.1.1 ...

###### Conceptual model

Further information: Statistical model, Parametric model,

**Nonparametric****statistics**, and Model selection. A statistical model is ... In**statistics**there can be models of mental events as well as models of physical events. For example, a statistical model of ... A**nonparametric**model has a distribution function without parameters, such as in bootstrapping, and is only loosely confined by ... and may be done with**nonparametric**means, such as with cross validation. ...###### Decomposition of time series

**Nonparametric**anova *1-way (Kruskal-Wallis). *2-way (Friedman). *Ordered alternative (Jonckheere-Terpstra) ... Rank

**statistics**. *Sign *Sample median. *Signed rank (Wilcoxon) *Hodges-Lehmann estimator. *Rank sum (Mann-Whitney) ...

###### Bayes estimator

Other loss functions are used in

**statistics**, particularly in robust**statistics**. Generalized Bayes estimators[edit]. See also: ... There are parametric and**non-parametric**approaches to empirical Bayes estimation. Parametric empirical Bayes is usually ... An alternative way of formulating an estimator within Bayesian**statistics**is maximum a posteriori estimation. ...###### k-nearest neighbors algorithm

"Consistent

**nonparametric**regression". Annals of**Statistics**. 5 (4): 595-620. doi:10.1214/aos/1176343886 ... "Annals of**Statistics**. 20 (3): 1236-1265. doi:10.1214/aos/1176348768.. *^ Mills, Peter (2012-08-09). "Efficient statistical ... In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a**non-parametric**method proposed by Thomas Cover used for ... Samworth, Richard J. (2012). "Optimal weighted nearest neighbour classifiers". Annals of**Statistics**. 40 (5): 2733-2763. arXiv: ...###### Principal component analysis

"Engineering

**Statistics**Handbook Section 6.5.5.2". Retrieved 19 January 2015.. *^ A.A. Miranda, Y.-A. Le Borgne, and G. Bontempi ...**Nonparametric**anova *1-way (Kruskal-Wallis). *2-way (Friedman). *Ordered alternative (Jonckheere-Terpstra) ... Shaw P.J.A. (2003) Multivariate**statistics**for the Environmental Sciences, Hodder-Arnold. ISBN 0-340-80763-6.[page needed] ... a b Jolliffe I.T. Principal Component Analysis, Series: Springer Series in**Statistics**, 2nd ed., Springer, NY, 2002, XXIX, 487 p ...###### Nonlinear optics

See Section Parametric versus

**Nonparametric**Processes, Nonlinear Optics by Robert W. Boyd (3rd ed.), pp. 13-15. ... Nonlinear effects fall into two qualitatively different categories, parametric and**non-parametric**effects. A parametric non- ...###### Spectral density

A common

**non-parametric**technique is the periodogram. The spectral density is usually estimated using Fourier transform methods ... The autocorrelation function is a**statistic**defined as ... estimation techniques can involve parametric or**non-parametric**...###### Probit model

In

**statistics**, a probit model is a type of regression where the dependent variable can take only two values, for example ...###### Sampling (**statistics**)

**Nonparametric**anova *1-way (Kruskal-Wallis). *2-way (Friedman). *Ordered alternative (Jonckheere-Terpstra) ...

**Statistics**.. *^ Anderson, Theodore (1951). "Classification by multivariate analysis". Psychometrika. 16 (1): 31-50. doi:10.1007 ... More mathematical

**statistics**is required for Lohr, for Särndal et alia, and for Cochran (classic[citation needed]): ... "Introduction to the Practice of

**Statistics**". *^ Freedman, David; Pisani, Robert; Purves, Roger. ...

**Nonparametric** **statistics**

... (Redirected from

**Non-parametric**).**Nonparametric****statistics**is the branch of**statistics**that is not ...**nonparametric****statistics**(in the sense of a**statistic**over data, which is defined to be a function on a sample that has no ... As such it is the opposite of parametric**statistics**. It includes**nonparametric**descriptive**statistics**, statistical models, ... Corder, G. W.; Foreman, D. I. (2014).**Nonparametric****Statistics**: A Step-by-Step Approach. Wiley. ISBN 978-1118840313.. ...**Nonparametric** **Statistics** | **Statistics** | Amherst College

**Statistics**. *

**Nonparametric**

**Statistics**.

**Nonparametric**

**Statistics**. Section Navigation. Sub Navigation. *

**Nonparametric**

**Statistics**... and the intuitive nature of

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**statistics**. Four class hours per week. ...

**Nonparametric**Statistical Methods. Wiley, 2013. Hollander, Wolfe, and Chicken. Amherst Books. TBD. ... We will also investigate correlation, regression, and one-way analysis of variance techniques in a

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Our aim is to rejuvenate the research activity in

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**Nonparametric** **statistics** - Wikipedia

**nonparametric**

**statistics**(a

**statistic**is defined to be a function on a sample; no dependency on a parameter). Order

**statistics**...

**Nonparametric**

**statistics**includes both descriptive

**statistics**and statistical inference.

**Nonparametric**tests are often used ...

**Nonparametric**

**statistics**is the branch of

**statistics**that is not based solely on parametrized families of probability ... Practical

**Nonparametric**

**Statistics**(Third ed.), Wiley, pp. 157-176, ISBN 0-471-16068-7 Sprent, P. (1989), Applied

**Nonparametric**...

**NONPARAMETRIC** **STATISTICS** 2018/2019 - Università di Bologna

**Non parametric**inference: the bootstrap..

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**Nonparametric**statistical methods, Wiley, New York, 2014, 3rd edition. ISBN: 978-0-470 ...

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**Nonparametric**

**statistics**. (Redirected from

**Non-parametric**).

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**nonparametric**

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**Nonparametric****Statistic**for Joint Mean-Variance Quality Control (October 23, 2010). ... A Powerful and Robust**Nonparametric****Statistic**for Joint Mean-Variance Quality Control. InterStat, September 2009 ... The**statistic**- OBMax2 - is not computationally intensive, and although initially designed for quality control testing in ... only one two-sample**statistic**that is not computationally intensive has been designed specifically for the one-sided test of Ho ...**Nonparametric** **statistics** | definition of **nonparametric** **statistics** by Medical dictionary

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**Nonparametric**methods now constitute one of the most successful branches of modern**statistics**," said Professor Puri. "The ... So theories and methods of**nonparametric****statistics**have evolved to handle data sets such as these. ... Hence, much of**statistics**is "parametric." A good example is the Gaussian, or "normal distribution," which is dependent on two ... And because**nonparametric**statistical techniques are valid under less restrictive assumptions than those of a specified ...###### topic:"**Statistics**, **nonparametric**" found 1640 records • Arctic Health

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Eubank, R.L. (1999)

**Nonparametric**regression and spline smoothing. Dekker.. Hardle, W. (1990) Applied**Nonparametric**Regression ...**Nonparametric**regression provides a very flexible approach to exploring the relationship between a response and an associated ... The test**statistic**of the general linear hypothesis and its distribution. Confidence intervals and prediction intervals. [5] ... derive key theoretical properties of both parametric and**nonparametric**estimators, such as the form of the estimators and their ...**nonparametric** | **Statistics** Help @ Talk **Stats** Forum

I run the

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###### Estimation15

- A variety of other topics may be explored in the nonparametric setting including resampling techniques (for example, bootstrapping), categorical data and contingency tables, density estimation, and the two-way layout. (amherst.edu)
- It covers theory, methodology, applications and computational aspects, addressing topics such as nonparametric curve estimation, regression smoothing, models for time series and more generally dependent data, varying coefficient models, symmetry testing, robust estimation, and rank-based methods for factorial design. (springer.com)
- The author also describes time-to-event nonparametric estimation methods, such as the Kaplan-Meier survival curve and Cox proportional hazards model, and presents histogram and kernel density estimation methods. (routledge.com)
- Applied Nonparametric Statistics in Reliability is focused on the use of modern statistical methods for the estimation of dependability measures of reliability systems that operate under different conditions. (buchfreund.de)
- In this paper, we develop a fully nonparametric approach for the estimation of the cumulative incidence function with Missing At Random right-censored competing risks data. (ssrn.com)
- This paper investigates nonparametric estimation of density on [0, 1]. (repec.org)
- Bayesian Approaches to Non-parametric Estimation of Densities on the Unit Interval ," Monash Econometrics and Business Statistics Working Papers 3/12, Monash University, Department of Econometrics and Business Statistics. (repec.org)
- Estimation of Hyperbolic Diffusion Using MCMC Method ," Monash Econometrics and Business Statistics Working Papers 18/02, Monash University, Department of Econometrics and Business Statistics. (repec.org)
- A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation ," Monash Econometrics and Business Statistics Working Papers 11/07, Monash University, Department of Econometrics and Business Statistics. (repec.org)
- Due to the curse of dimensionality, estimation in a multidimensional nonparametric regression model is in general not feasible. (uzh.ch)
- Nonparametric and semiparametric statistical methods provide a way to reduce the strength of the assumptions required for estimation and inference, thereby reducing the opportunities for obtaining misleading results. (springer.com)
- The literature on nonparametric and semiparametric estimation is large and highly technical. (springer.com)
- It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. (nih.gov)
- This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. (routledge.com)
- He is well known for his work on the theory and application of nonparametric curve estimation and is the author of Nonparametric Curve Estimation: Methods, Theory, and Applications . (routledge.com)

###### Journal of Nonparametric Statistics2

- The ISNPS 2018 conference in Salerno was organized with the support of the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and the University of Salerno. (springer.com)
- JOURNAL OF NONPARAMETRIC STATISTICS provides a medium for the publication of research and survey work in the area of nonparametric statistics. (periodicals.com)

###### 20171

- Receive email alerts on new books, offers and news in Statistics & Probability 2017 Catalogue. (cambridge.org)

###### Inference4

- Nonparametric statistics includes both descriptive statistics and statistical inference. (wikipedia.org)
- By the end of the course the student knows the fundamentals of the most relevant nonparametric techniques for statistical inference. (unibo.it)
- A concrete modelling scheme is chosen for each practical situation and, in consequence, a nonparametric inference procedure is conducted. (buchfreund.de)
- 15-2 CHAPTER 15 Nonparametric Tests Introduction The most commonly used methods for inference about the means of quan-titativeresponse variables assume that the variables in question have nor-maldistributions in the population or populations from which we draw our data. (sputtr.com)

###### Abstract2

- Nonparametric Regression Analysis of Longitudinal Data Version: Sept. 22,2003 Jane-Ling Wang Department of Statistics, University of California, Davis, CA 95616, U.S.A. Email: [email protected] Abstract. (sputtr.com)
- Abstract: We propose a new nonparametric test for the supposition of independencebetween two continuous random variables. (duhnnae.com)

###### Econometrics2

- Receive email alerts on new books, offers and news in Statistics for econometrics, finance and insurance. (cambridge.org)
- He is the author of over 100 journal articles and book chapters in econometrics and statistics, a winner of the Richard Stone prize in applied econometrics, a fellow of the Econometric Society and American Statistical Association, and a former co-editor of Econometrica . (springer.com)

###### 20181

- Highlighting the latest advances in nonparametric and semiparametric statistics, this book gathers selected peer-reviewed contributions presented at the 4th Conference of the International Society for Nonparametric Statistics (ISNPS), held in Salerno, Italy, on June 11-15, 2018. (springer.com)

###### Parametric tests3

- Nonparametric tests are often used when the assumptions of parametric tests are violated. (wikipedia.org)
- I was thinking about analysing this data with the statistical model ANOVA, using non-parametric tests or Bayesian statistics. (talkstats.com)
- Nonparametric Tests 3.1 Introduction Nonparametric , or distribution free tests are so-called because the assumptions underlying their use are "fewer and weaker than those associated with parametric tests" (Siegel & Castellan, 1988, p. 34). (sputtr.com)

###### Modern nonparametric1

- He is active in modern nonparametric statistics research fields, including functional analysis, sequential methods, and complex system applications. (wiley.com)

###### Approaches5

- Order statistics , which are based on the ranks of observations, are one example of such statistics and these play a central role in many nonparametric approaches. (wikipedia.org)
- Gaussian Process Regression and Kernel Ridge Regression are popular nonparametric regression approaches. (wias-berlin.de)
- The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. (wiley.com)
- use the statistical software R to analyse real data using both parametric and nonparametric approaches. (manchester.ac.uk)
- An emphasis has been on latent variable models, nonparametric approaches and geometrically based models. (warwick.ac.uk)

###### Fully nonparametric1

- New test procedures are presented under fully nonparametric models for the two-factor mixed and random effects designs. (hindawi.com)

###### Popular nonparametric1

- The purpose of the book is to teach master's students applications of popular nonparametric methods making use of SAS 9.3 software. (routledge.com)

###### Semiparametric1

- This book presents the main ideas underlying a variety of nonparametric and semiparametric methods. (springer.com)

###### Mathematics6

- In the Research Excellence Framework (REF) 2014, research by the School of Mathematics, Statistics and Actuarial Science was ranked 25th in the UK for research power and 100% or our research was judged to be of international quality. (kent.ac.uk)
- An introduction to the mathematics needed for students who plan to take MATH 2208 and MATH 2209 (Introduction to Statistics I and II). (msvu.ca)
- Restriction B: Not open to students who have taken or are taking MATH 123 , MATH 130 or MATH 131 , except by permission of the Department of Mathematics and Statistics. (mcgill.ca)
- Mathematics & Statistics (Sci) : Review of trigonometry and other Precalculus topics. (mcgill.ca)
- Mathematics & Statistics (Sci) : Review of functions and graphs. (mcgill.ca)
- Mathematics & Statistics (Sci) : The definite integral. (mcgill.ca)

###### 20163

- by Sabrina exist statistical Nonparametric Statistics: 2nd ISNPS, Cádiz, June 2014 2016 and network from your researchers! (5senkels.de)
- hemodynamic Nonparametric Statistics: 2nd ISNPS, Cádiz, June 2014 2016 is extended for the time of single T children. (5senkels.de)
- If you are at an Nonparametric Statistics: 2nd ISNPS, Cádiz, June 2014 2016 or responsible definition, you can get the access testing to involve a metric across the heart planning for standard or other devices. (5senkels.de)

###### Data31

- The first meaning of nonparametric covers techniques that do not rely on data belonging to any particular parametric family of probability distributions. (wikipedia.org)
- The course will emphasize data analysis (with appropriate use of statistical software) and the intuitive nature of nonparametric statistics. (amherst.edu)
- nonparametric statistics (in the sense of a statistic over data, which is defined to be a function on a sample that has no dependency on a parameter ), whose interpretation does not depend on the population fitting any parameterised distributions. (wikipedia.org)
- What do you do when you realize that the data set from the study that you have just completed violates the sample size or other requirements needed to apply parametric statistics? (sagepub.com)
- It also discusses nonparametric and permutation solutions for several different types of data, including ordinal data, spatial data, survival data and the joint modeling of both longitudinal and time-to-event data, permutation and resampling techniques, and practical applications of nonparametric statistics. (springer.com)
- Designed for a graduate course in applied statistics, Nonparametric Methods in Statistics with SAS Applications teaches students how to apply nonparametric techniques to statistical data. (routledge.com)
- The proposed formulation generalizes the joint point estimator and variance models to explicitly parameterize a multiplicative bias in observed variances under a nonparametric formulation that allows the data to discover distinct bias regimes. (bls.gov)
- Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. (wiley.com)
- Just like Newton's laws which are not applicable near the speed of light or in situations where quantum mechanics must be used, parametric statistics fall apart when a data set's distribution is unknown or wildly erratic. (iu.edu)
- So theories and methods of nonparametric statistics have evolved to handle data sets such as these. (iu.edu)
- I am working with nonparametric data and I was trying to apply a Mardia-Watson-Wheeler uniform-scores test to 2 or more different classes of data to check if they come from the same population. (talkstats.com)
- I think I am pretty clear on the differences between parametric and nonparametric tests and which is more appropriate to use given the data you have collected. (talkstats.com)
- The Kruskal-Wallis test uses the same method but, as with many nonparametric tests, the ranks of the data are used in place of the raw data. (biomedcentral.com)
- Nonparametric statistics has probably become the leading methodology for researchers performing data analysis. (buchfreund.de)
- Inferential statistics help us decide, for example, whether the differences between groups that we see in our data are strong enough to provide support for our hypothesis that group differences exist in general, in the entire population. (coursera.org)
- An important class of nonparametric tests employs the ordinal properties of the data. (uchicago.edu)
- Six Sigma Statistics with Excel and Minitab offers a complete guide to Six Sigma statistical methods, plus expert coverage of Excel and Minitab, two of today's most popular programs for statistical analysis and data visualization. (indigo.ca)
- In addition, Six Sigma Statistics with Excel and Minitab enables you to develop a better understanding of the Taguchi Method…use measurement system analysis to find out if measurement processes are accurate…discover how to test ordinal or nominal data with nonparametric statistics…and apply the full range of basic quality tools. (indigo.ca)
- Next new nonparametric multivariate two sample and multisample tests are developed based on directions of differences between paired data, each member of a pair being from different samples. (illinois.edu)
- Finally we apply this method to extend Kendall's $\tau$ to a multivariate setting and develop nonparametric multiple and multivariate regression techniques based on directions of data. (illinois.edu)
- The Kendall-Theil robust line was selected because this robust nonparametric method is resistant to the effects of outliers and nonnormality in residuals that commonly characterize hydrologic data sets. (usgs.gov)
- The program was developed to provide regression equations with an error component for stochastic data generation because nonparametric multisegment regression tools are not available with the software that is commonly used to develop regression models. (usgs.gov)
- Introduction to Nonparametric Statistics Craig L. Scanlan, EdD, RRT Parametric statistics assume (1) that the distribution characteristics of a sample's population are known (e.g. the mean, standard deviation, normality) and (2) that the data being analyzed are at the interval or ratio level. (sputtr.com)
- Two nonparametric methods for the identification of subgroups with outstanding outcome values are described and compared to each other in a simulation study and an application to clinical data. (nih.gov)
- In the second year, stochastic models and processes, Bayesian statistics and the analysis of large data sets are among the range of topics explored. (kent.ac.uk)
- This paper investigates the problem of computing nonparametric correlations on the fly for streaming data. (arxiv.org)
- To compute these statistics, the mean yield data have to be transformed into ranks for each genotype and environment, and the genotypes are considered stable if their ranks are similar across environments. (manzik.com)
- Nonparametric regression is a category of regression analysis in which the predictor does not take a predetermined form but is constructed according to information derived from the data. (rug.nl)
- Nonparametric regression requires larger sample sizes than regression based on parametric models because the data must supply the model structure as well as the model estimates. (rug.nl)
- Example of a curve (red line) fit to a small data set (black points) with nonparametric regression using a Gaussian kernel smoother. (rug.nl)
- The three nonparametric measures of phenotypic stability Si (1), Si (2) and Si (3) introduced and discussed in Huehn (1990) and the classical parameters: environmental variance, ecovalence, regression coefficient, and sum of squared deviations from regression were computed for winter wheat grain yield data from the official registration trials (1974, 1975 and 1976) in the Federal Republic of Germany. (semanticscholar.org)

###### Variances2

- consider nonparametric lack-of-ﬁt tests in presence of heteroscedastic variances. (k-state.edu)
- The test statistic turns out to be the "F" statistic that we saw when we looked at when comparing variances. (nmculturenet.org)

###### Theory10

- a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. (ecampus.com)
- Introduction to the theory of nonparametric statistics by R.H. Randles and D.A. Wolfe, Wiley. (epfl.ch)
- Robust Statistics: Theory and Methods by D.R. Martin, M. Salibian-Barrera, R.A. Maronna, V.J. Yohai, Wiley. (epfl.ch)
- In statistics and probability theory, the nonparametric skew is a statistic occasionally used with random variables that take real values. (wikipedia.org)
- The asymptotic theory of the test statistics is derived under the Neyman-Scott framework, in the sense that the number of levels of both factors is large but the group sizes can remain fixed. (hindawi.com)
- Mathematical theory can help to understand the performance and limitations of nonparametric Bayes procedures. (warwick.ac.uk)
- Communications in Statistics - Theory and Methods 49 (3): 697-725. (dur.ac.uk)
- Communications in Statistics - Theory and Methods 47 (10): 2527-2548. (dur.ac.uk)
- As with the bestselling first edition, "Computational Statistics Handbook with MATLAB" makes computational statistics as accessible as possible by playing down theory and building an understanding of the algorithms used in a wide range of applications. (worldcat.org)
- Provides access to computational statistics by playing down theory and building an understanding of the algorithms used in a wide range of applications. (worldcat.org)

###### Biostatistics1

- It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge such as biostatistics or social sciences, nonparametric analyses in reliability currently form an interesting area of study that has not yet been fully explored. (buchfreund.de)

###### Inferences2

- The process of drawing inferences, making predictions, and testing significance are examples of inferential statistics. (thefreedictionary.com)
- Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. (coursera.org)

###### Tests7

- He is the author and creator of the NonParametric Combination Test software for multivariate and multistrata permutation tests. (springer.com)
- The text begins with classical nonparametric hypotheses testing, including the sign, Wilcoxon sign-rank and rank-sum, Ansari-Bradley, Kolmogorov-Smirnov, Friedman rank, Kruskal-Wallis H, Spearman rank correlation coefficient, and Fisher exact tests. (routledge.com)
- I need to choose a good dataset with at least two variables because I'll need to compare them by calculating measures of association, performing two-sample tests and maybe doing a nonparametric regression on R, ... Therefore, I was thinking about choosing a dataset about COVID 19 because. (talkstats.com)
- In this section, I want to discuss Nonparametric tests. (coursera.org)
- In most nonparametric statistical tests, the original scores or observations are replaced by another variable containing less information. (uchicago.edu)
- They are also competitive among other nonparametric tests when samples are from light tailed distributions. (illinois.edu)
- A novel presentation of rank and permutation tests, with accessible guidance to applications in R Nonparametric testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. (worldcat.org)

###### Bayesian Statistics1

- This master class on Nonparametric Bayesian Statistics will consist of 4 lectures each from two speakers who are leaders of the field, David Dunson (Duke University) and Harry van Zanten (University of Amsterdam). (warwick.ac.uk)

###### 20201

- On May 12, 2020 Kirill Efimov successfully defended his dissertation 'Adaptive nonparametric clustering' at Humboldt-Universität zu Berlin (supervisor Vladimir Spokoiny). (wias-berlin.de)

###### ISNPS3

- This volume is composed of peer-reviewed papers that have developed from the First Conference of the International Society for Non Parametric Statistics (ISNPS). (bookdepository.com)
- Nonparametric Statistics: 2nd ISNPS, Cádiz, June to Risk Factors to Remember book software, download, and contents that carry your quotation of getting a blood with a precise scan network. (5senkels.de)
- The Spotahome Blog They will analyze an Nonparametric Statistics: 2nd ISNPS, Cádiz, June 2014 from The Great Courses allowing them of your role. (5senkels.de)

###### Hypothesis2

- The test statistic of the general linear hypothesis and its distribution. (manchester.ac.uk)
- Decision Rule The decision will be to reject the null hypothesis if the test statistic from the table is greater than the F critical value with k-1 numerator and N-k denominator degrees of freedom. (nmculturenet.org)

###### Test8

- The statistic - OBMax2 - is not computationally intensive, and although initially designed for quality control testing in regulatory telecommunications, its range of application is as broad as the number of quality control settings requiring a one-sided test of the first two moments. (ssrn.com)
- The Kruskal-Wallis test is the nonparametric alternative to one-way analysis of variance, which is used to test for differences between more than two populations when the samples are independent. (biomedcentral.com)
- As can be seen, there is very little difference between the unadjusted and the adjusted test statistics because the number of ties is relatively small. (biomedcentral.com)
- We will start by considering the basic principles of significance testing: the sampling and test statistic distribution, p-value, significance level, power and type I and type II errors. (coursera.org)
- Hotelling and Solomons considered the distribution of the test statistic D = n ( m − a ) s {\displaystyle D={\frac {n(m-a)}{s}}} where n is the sample size, m is the sample mean, a is the sample median and s is the sample's standard deviation. (wikipedia.org)
- Review "Goodness-of-Fit" and the three "Non-parametric" test videos in the Calculations section of the "Statistics Visual Learner" media piece. (payloadz.com)
- A+ Tutorials PSY-520 Module 8 Exercises Graduate Statistics - Analysis of Variance GCU Review 'Goodness-of-Fit' and the three 'Non-parametric' test videos in the Calculations section of the 'Statistics Visual Learner' media piece. (payloadz.com)
- The calculation to arrive at the test statistic is quite complicated, hence we will assume that either the reader will be looking at a textbook for this, or rely on a computer. (nmculturenet.org)

###### Mathematical5

- Image processing tools based on mathematical algorithms from statistics or variational methods enable a bulk of applications in the medical sciences. (wias-berlin.de)
- The first year of the programme gives you a strong background in statistics, including its mathematical aspects, equivalent to the Graduate Diploma in Statistics. (kent.ac.uk)
- The ever increasing use of nonparametric Bayesian methods raises all kinds of interesting theoretical, mathematical questions. (warwick.ac.uk)
- Since 2012 he is professor of Mathematical Statistics at the University of Amsterdam. (warwick.ac.uk)
- Professor Sam Efromovich is a Fellow of the Institute of Mathematical Statistics and the American Statistical Association. (routledge.com)

###### Analysis5

- We will also investigate correlation, regression, and one-way analysis of variance techniques in a nonparametric setting. (amherst.edu)
- And because nonparametric statistical techniques are valid under less restrictive assumptions than those of a specified distribution type, they are very versatile, and they have found applications in many new methods of analysis. (iu.edu)
- It is the nonparametric alternative to one-way analysis of variance. (biomedcentral.com)
- Welfare Analysis of Changing Food Prices: A Nonparametric Examination of Export Ban on Rice in India ," Working Papers 177, Department of Economics, SOAS, University of London, UK. (repec.org)
- Our analysis suggests that the link between IT and increased productivity emerged well before the recent surge in the aggregate productivity statistics and that the current macroeconomic productivity revival may in part reflect the contributions of intangible capital accumulated in the past. (psu.edu)

###### Wiley2

###### Normality1

- We obtain results on the pointwise asymptotic normality as well as the uniform convergence rate of the proposed nonparametric estimator. (ssrn.com)

###### Distributions4

- Nonparametric statistics is the branch of statistics that is not based solely on parametrized families of probability distributions (common examples of parameters are the mean and variance). (wikipedia.org)
- Nonparametric statistics is the branch of statistics that is not based solely on parameterized families of probability distributions (common examples of parameters are the mean and variance). (wikipedia.org)
- The proposed Bayesian nonparametric approach takes advantage of the flexibility of Dirichlet process mixtures to achieve any continuous deformation of linearly combined predictive distributions. (arxiv.org)
- Nonparametric statistics for health care research : statistics for small samples and unusual distributions / Marjorie A. Pett. (who.int)

###### Outcomes1

- Nonparametric Statistics for Health Care Research was developed for such scenarios-research undertaken with limited funds, often using a small sample size, with the primary objective of improving client care and obtaining better client outcomes. (sagepub.com)

###### Models4

- Following the tradition of Carleton University yet another International Conference on Nonparametric methods for Measurement Error Models and Related topics has been arranged. (utoronto.ca)
- It then discusses smoothing techniques (loess and thin-plate splines) for classical nonparametric regression as well as binary logistic and Poisson models. (routledge.com)
- Dosses ringleted bayesian nonparametric hidden markov models deforming anagogically? (iklanposkota.tk)
- Nonparametric Regression STATA 15, nonparametric regression STATA 15 models canshaped any function, either linear or nonlinear. (statisticsforum.com)

###### Estimates5

- The relationship of our statistics to Chaudhuri's location estimates based on U-statistics is discussed. (illinois.edu)
- The Kendall-Theil Robust Line software (KTRLine-version 1.0) is a Visual Basic program that may be used with the Microsoft Windows operating system to calculate parameters for robust, nonparametric estimates of linear-regression coefficients between two continuous variables. (usgs.gov)
- Regression statistics such as the median error, the median absolute deviation, the prediction error sum of squares, the root mean square error, the confidence interval for the slope, and the bias correction factor for median estimates are calculated by use of nonparametric methods. (usgs.gov)
- The local polynomial periodogram enables one to obtain nonparametric estimates of the instantaneous frequency (IF) and its derivatives. (unisa.ac.za)
- We analyse the properties of nonparametric spectral estimates when applied to long memory and trending nonstationary multiple time series. (uc3m.es)

###### 20191

- 2019. STABILITYSOFT: A new online program to calculate parametric and non-parametric stability statistics for crop traits. (manzik.com)

###### Kernel1

- A nonparametric kernel regression model is employed to estimate the relation between the scaled environmental and economic factors, which are determined as regression variables. (mdpi.com)

###### Estimator2

###### Correlations3

- Nonparametric correlations such as Spearman's rank correlation and Kendall's tau correlation are widely applied in scientific and engineering fields. (arxiv.org)
- This paper proposes a novel online algorithm for computing nonparametric correlations. (arxiv.org)
- The online algorithm can compute the nonparametric correlations 10 to 1,000 times faster than the corresponding batch algorithm, and it can compute them based either on all past observations or on fixed-size sliding windows. (arxiv.org)

###### Density1

- The weak posterior consistency of the Bayesian nonparametric calibration is provided under suitable conditions for unknown true density. (arxiv.org)

###### Search2

- Weiterlesen In download Practical Nonparametric Statistics, to male agency Included on the search chemistry, it has identifying Evangelical thoughtways' into T of method which is 2000-01-12T12:00:00Full file modes. (enddarmpraxis-muenster.de)
- WHO HQ Library catalog › Results of search for 'su:{Statistics, Nonparametric. (who.int)

###### Annals2

###### Introductory statistics2

- It also deserves a place in libraries of all institutions where introductory statistics courses are taught. (ecampus.com)
- Elementary Statistics: A Step By Step Approach is for introductory statistics courses with a basic algebra prerequisite. (ecampus.com)

###### Variance1

- The coefficient of variation is suggested by Francis and Kannenberg (1987) as a stability statistic through the combination of the coefficient of variation, mean yield, and environmental variance. (manzik.com)

###### Introduction4

- This course is an introduction to nonparametric and distribution-free statistical procedures and techniques. (amherst.edu)
- Higgins, James (2004), Introduction to Nonparametric Statistics 2. (sputtr.com)
- In particular it will prepare those who plan to take MATH 2208 (Introduction to Statistics I) and/or MATH 1102 (Precalculus I). (msvu.ca)
- Statistics in a Nutshell is a clear and concise introduction and reference that's perfect for anyone with no previous background in the subject. (oreilly.com)

###### Genotypes4

- In this study, 6 six stability measures consisting of 4 parametric and 2 nonparametric were used to evaluate the genotype by environment interaction (GEI) in 20 durum wheat genotypes. (comu.edu.tr)
- Both parametric (b(i), S-di(2), R-i(2), P-i) and nonparametric (S-i((1)), S-i((2))) univariate stability statistics were used to determine stability of the durum wheat genotypes. (comu.edu.tr)
- According to this statistic, the genotypes that show higher values for the θ (i) are considered more stable. (manzik.com)
- According to this statistic, genotypes with minimum values are intended to be more stable. (manzik.com)

###### Techniques5

- Covering the most commonly used nonparametric statistical techniques available in statistical packages and on open-resource statistical websites, this well-organized and accessible Second Edition helps readers, including those beyond the health sciences field, to understand when to use a particular nonparametric statistic, how to generate and interpret the resulting computer printouts, and how to present the results in table and text format. (sagepub.com)
- Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. (wiley.com)
- Essential for achieving Six Sigma goals in any organization, Six Sigma Statistics with Excel and Minitab is a unique, skills-building toolkit for mastering a wide range of vital statistical techniques, and for capitalizing on the potential of Excel and Minitab. (indigo.ca)
- Authoritative and comprehensive, Six Sigma Statistics with Excel and Minitab is a valuable skills-building resource for mastering all the statistical techniques for Six Sigma operations, while harnessing the power of Excel and Minitab. (indigo.ca)
- With Statistics in a Nutshell , you learn how to perform most common statistical analyses, and understand statistical techniques presented in research articles. (oreilly.com)

###### Wolfe1

- DOUGLAS A. WOLFE is Professor and Chair Emeritus in the Department of Statistics at Ohio State University in Columbus. (wiley.com)