###### Statistics, Nonparametric

###### Models, Statistical

###### Genetic Linkage

###### Lod Score

###### Data Interpretation, Statistical

###### Statistics as Topic

###### Computer Simulation

###### Biometry

###### Models, Genetic

###### Algorithms

###### Chromosome Mapping

###### Bayes Theorem

###### Genetic Markers

###### Likelihood Functions

###### Pedigree

###### Reproducibility of Results

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

###### Monte Carlo Method

###### Genetic Heterogeneity

###### Genome, Human

###### Sample Size

###### Microsatellite Repeats

###### Genetic Predisposition to Disease

###### Matched-Pair Analysis

###### Biostatistics

###### Software

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

###### Regression Analysis

###### 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)

###### 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

###### Cluster Analysis

###### Linkage Disequilibrium

###### Case-Control Studies

###### Epistasis, Genetic

###### Genome-Wide Association Study

###### Phenotype

###### Longitudinal Studies

###### Pattern Recognition, Automated

###### Cohort Studies

###### False Positive Reactions

###### Age of Onset

###### Predictive Value of Tests

###### Image Enhancement

###### Retrospective Studies

###### Risk Factors

###### Nonlinear Dynamics

###### Risk Assessment

###### Questionnaires

###### Polymorphism, Single Nucleotide

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

###### Computational Biology

###### Multivariate Analysis

###### Cross-Sectional Studies

###### Sex Factors

###### Prospective Studies

###### Logistic Models

###### Quality Control

###### Genome

###### Survival Analysis

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

###### Principal Component Analysis

###### Treatment Outcome

###### Area Under Curve

###### Pregnancy

###### European Continental Ancestry Group

###### Databases, Factual

###### 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

###### Biological Markers

###### Death Certificates

###### Breeding

###### Brain

###### Gene Frequency

###### Incidence

###### Genetic Loci

###### Clinical Trials as Topic

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

###### Follow-Up Studies

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

###### Chi-Square Distribution

###### Neoplasms

###### Proportional Hazards Models

###### Nephelometry and Turbidimetry

###### Space-Time Clustering

###### Physical Chromosome Mapping

###### Observer Variation

###### Prevalence

###### Severity of Illness Index

###### Prognosis

###### Statistical Distributions

###### Diabetes Mellitus, Type 2

###### 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

###### Schizophrenia

###### HIV Infections

###### Alcoholism

###### Age Distribution

###### Poisson Distribution

###### Quality of Life

###### Registries

###### Population Surveillance

###### Sex Distribution

###### Canada

###### Tumor Markers, Biological

###### Brain Neoplasms

###### Demography

###### Obesity

###### Double-Blind Method

###### Socioeconomic Factors

###### Wounds and Injuries

###### Lupus Erythematosus, Systemic

###### Mutation

###### Health Surveys

###### Geographic Information Systems

###### Poisoning

###### Birth Certificates

###### Life Expectancy

###### Infant Mortality

###### International Classification of Diseases

###### Nature

###### Geography

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

###### Diffusion Tensor Imaging

###### Anisotropy

## 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)**Genetic predisposition to disease**refers to an individual's inherited genetic makeup that increases their risk of developing a particular disease or health condition.

Genetic predisposition to disease refers to the tendency of an individual to develop a particular disease or condition due to their genetic makeup. It means that certain genes or combinations of genes increase the risk of developing a particular disease or condition. Genetic predisposition to disease is not the same as having the disease itself. It simply means that an individual has a higher likelihood of developing the disease compared to someone without the same genetic predisposition. Genetic predisposition to disease can be inherited from parents or can occur due to spontaneous mutations in genes. Some examples of genetic predisposition to disease include hereditary breast and ovarian cancer, Huntington's disease, cystic fibrosis, and sickle cell anemia. Understanding genetic predisposition to disease is important in medical practice because it can help identify individuals who are at high risk of developing a particular disease and allow for early intervention and prevention strategies to be implemented.

**Genetic diseases, inborn**are disorders caused by mutations in an individual's DNA that are present from birth and can be inherited from parents.

Inborn genetic diseases, also known as genetic disorders or hereditary diseases, are conditions that are caused by mutations or variations in an individual's DNA. These mutations can be inherited from one or both parents and can affect the normal functioning of the body's cells, tissues, and organs. Inborn genetic diseases can be classified into several categories, including single-gene disorders, chromosomal disorders, and multifactorial disorders. Single-gene disorders are caused by mutations in a single gene, while chromosomal disorders involve changes in the number or structure of chromosomes. Multifactorial disorders are caused by a combination of genetic and environmental factors. Examples of inborn genetic diseases include cystic fibrosis, sickle cell anemia, Huntington's disease, Down syndrome, and Turner syndrome. These diseases can have a wide range of symptoms and severity, and can affect various parts of the body, including the heart, lungs, brain, and skeletal system. Diagnosis of inborn genetic diseases typically involves a combination of medical history, physical examination, and genetic testing. Treatment options may include medications, surgery, and supportive care, depending on the specific disease and its severity.

**Prostatic neoplasms**refer to tumors or abnormal growths that develop in the prostate gland, which is a male reproductive organ.

Prostatic neoplasms refer to tumors that develop in the prostate gland, which is a small gland located in the male reproductive system. These tumors can be either benign (non-cancerous) or malignant (cancerous). Benign prostatic neoplasms, also known as benign prostatic hyperplasia (BPH), are the most common type of prostatic neoplasm and are typically associated with an increase in the size of the prostate gland. Malignant prostatic neoplasms, on the other hand, are more serious and can spread to other parts of the body if left untreated. The most common type of prostate cancer is adenocarcinoma, which starts in the glandular cells of the prostate. Other types of prostatic neoplasms include sarcomas, which are rare and start in the connective tissue of the prostate, and carcinoid tumors, which are rare and start in the neuroendocrine cells of the prostate.

**Breast neoplasms**are abnormal growths or tumors in the breast tissue, which can be benign or malignant.

Breast neoplasms refer to abnormal growths or tumors in the breast tissue. These growths can be benign (non-cancerous) or malignant (cancerous). Benign breast neoplasms are usually not life-threatening, but they can cause discomfort or cosmetic concerns. Malignant breast neoplasms, on the other hand, can spread to other parts of the body and are considered a serious health threat. Some common types of breast neoplasms include fibroadenomas, ductal carcinoma in situ (DCIS), invasive ductal carcinoma, and invasive lobular carcinoma.

**Neoplasms**are abnormal growths of cells that can be benign or malignant and may form tumors.

In the medical field, neoplasms refer to abnormal growths or tumors of cells that can occur in any part of the body. These growths can be either benign (non-cancerous) or malignant (cancerous). Benign neoplasms are usually slow-growing and do not spread to other parts of the body. They can cause symptoms such as pain, swelling, or difficulty moving the affected area. Examples of benign neoplasms include lipomas (fatty tumors), hemangiomas (vascular tumors), and fibromas (fibrous tumors). Malignant neoplasms, on the other hand, are cancerous and can spread to other parts of the body through the bloodstream or lymphatic system. They can cause a wide range of symptoms, depending on the location and stage of the cancer. Examples of malignant neoplasms include carcinomas (cancers that start in epithelial cells), sarcomas (cancers that start in connective tissue), and leukemias (cancers that start in blood cells). The diagnosis of neoplasms typically involves a combination of physical examination, imaging tests (such as X-rays, CT scans, or MRI scans), and biopsy (the removal of a small sample of tissue for examination under a microscope). Treatment options for neoplasms depend on the type, stage, and location of the cancer, as well as the patient's overall health and preferences.

**Diabetes Mellitus, Type 2**is a chronic metabolic disorder characterized by insulin resistance and relative insulin deficiency, leading to elevated blood glucose levels.

Diabetes Mellitus, Type 2 is a chronic metabolic disorder characterized by high blood sugar levels due to insulin resistance and relative insulin deficiency. It is the most common form of diabetes, accounting for about 90-95% of all cases. In type 2 diabetes, the body's cells become resistant to insulin, a hormone produced by the pancreas that helps regulate blood sugar levels. As a result, the pancreas may not produce enough insulin to overcome this resistance, leading to high blood sugar levels. The symptoms of type 2 diabetes may include increased thirst, frequent urination, fatigue, blurred vision, slow-healing sores, and unexplained weight loss. If left untreated, type 2 diabetes can lead to serious complications such as heart disease, stroke, kidney disease, nerve damage, and vision loss. Treatment for type 2 diabetes typically involves lifestyle changes such as diet and exercise, as well as medication to help regulate blood sugar levels. In some cases, insulin therapy may be necessary.

**Bipolar disorder**is a mental health condition characterized by extreme mood swings, including episodes of mania and depression.

Bipolar disorder, also known as manic-depressive illness, is a mental health condition characterized by extreme mood swings that include episodes of mania or hypomania (abnormally elevated or irritable mood) and depression. These mood swings can be severe and can significantly impact a person's daily life, relationships, and ability to function. Bipolar disorder is typically diagnosed based on a person's symptoms, medical history, and a physical examination. There are several different types of bipolar disorder, including bipolar I disorder, bipolar II disorder, cyclothymic disorder, and other specified bipolar and related disorders. Treatment for bipolar disorder typically involves a combination of medication and therapy. Medications used to treat bipolar disorder may include mood stabilizers, antipsychotics, and antidepressants. Therapy may include cognitive-behavioral therapy, interpersonal and social rhythm therapy, and family-focused therapy. It is important to note that bipolar disorder is a serious medical condition that requires ongoing treatment and management. With proper treatment, many people with bipolar disorder are able to manage their symptoms and lead fulfilling lives.

**Schizophrenia**is a chronic and severe mental disorder characterized by hallucinations, delusions, disorganized thinking, and abnormal behavior.

Schizophrenia is a severe mental disorder characterized by a range of symptoms that affect a person's thoughts, emotions, and behavior. These symptoms can include hallucinations (hearing or seeing things that are not there), delusions (false beliefs that are not based in reality), disorganized thinking and speech, and problems with emotional expression and social interaction. Schizophrenia is a chronic condition that can last for a lifetime, although the severity of symptoms can vary over time. It is not caused by a single factor, but rather by a complex interplay of genetic, environmental, and neurobiological factors. Treatment for schizophrenia typically involves a combination of medication, therapy, and support from family and friends. While there is no cure for schizophrenia, with proper treatment, many people are able to manage their symptoms and lead fulfilling lives.

**HIV Infections**are caused by the Human Immunodeficiency Virus and lead to a weakened immune system, making individuals more susceptible to opportunistic infections and certain cancers.

HIV (Human Immunodeficiency Virus) infections refer to the presence of the HIV virus in the body. HIV is a retrovirus that attacks and weakens the immune system, making individuals more susceptible to infections and diseases. HIV is transmitted through contact with infected bodily fluids, such as blood, semen, vaginal fluids, and breast milk. The most common modes of transmission include unprotected sexual contact, sharing needles or syringes, and from mother to child during pregnancy, childbirth, or breastfeeding. HIV infections can be diagnosed through blood tests that detect the presence of the virus or antibodies produced in response to the virus. Once diagnosed, HIV can be managed with antiretroviral therapy (ART), which helps to suppress the virus and prevent the progression of the disease to AIDS (Acquired Immune Deficiency Syndrome). It is important to note that HIV is not the same as AIDS. HIV is the virus that causes AIDS, but not everyone with HIV will develop AIDS. With proper treatment and management, individuals with HIV can live long and healthy lives.

**Alcoholism**is a chronic and often relapsing brain disorder characterized by the excessive and compulsive consumption of alcohol despite its negative consequences.

Alcoholism, also known as alcohol use disorder (AUD), is a chronic and often relapsing brain disorder characterized by the excessive and compulsive consumption of alcohol despite negative consequences to one's health, relationships, and daily life. In the medical field, alcoholism is diagnosed based on a set of criteria outlined in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). These criteria include: 1. The presence of tolerance, which is the need to consume more alcohol to achieve the same desired effect. 2. The presence of withdrawal symptoms when alcohol use is reduced or stopped. 3. The presence of cravings or a strong desire to drink. 4. The continuation of alcohol use despite negative consequences, such as health problems, relationship problems, or legal problems. 5. The presence of significant impairment in social, occupational, or other important areas of functioning due to alcohol use. Alcoholism is a complex disorder that can be caused by a combination of genetic, environmental, and psychological factors. Treatment for alcoholism typically involves a combination of behavioral therapy, medication, and support groups.

**Brain neoplasms**are abnormal growths of cells in the brain or spinal cord.

Brain neoplasms, also known as brain tumors, are abnormal growths of cells in the brain. They can be either benign (non-cancerous) or malignant (cancerous). Brain tumors can occur in any part of the brain and can be primary (originating from brain cells) or secondary (spreading from other parts of the body to the brain). Symptoms of brain neoplasms can vary depending on the location and size of the tumor, but may include headaches, seizures, changes in vision or hearing, difficulty with balance or coordination, and changes in personality or behavior. Diagnosis of brain neoplasms typically involves a combination of imaging tests such as MRI or CT scans, as well as a biopsy to confirm the presence of cancer cells. Treatment options for brain neoplasms may include surgery, radiation therapy, chemotherapy, or a combination of these approaches. The specific treatment plan will depend on the type, location, and stage of the tumor, as well as the overall health of the patient.

**Obesity**is a medical condition characterized by excessive accumulation of body fat that increases the risk of various health problems.

Obesity is a medical condition characterized by an excessive accumulation of body fat, which increases the risk of various health problems. The World Health Organization (WHO) defines obesity as a body mass index (BMI) of 30 or higher, where BMI is calculated as a person's weight in kilograms divided by their height in meters squared. Obesity is a complex condition that results from a combination of genetic, environmental, and behavioral factors. It can lead to a range of health problems, including type 2 diabetes, heart disease, stroke, certain types of cancer, and respiratory problems. In the medical field, obesity is often treated through a combination of lifestyle changes, such as diet and exercise, and medical interventions, such as medications or bariatric surgery. The goal of treatment is to help individuals achieve and maintain a healthy weight, reduce their risk of health problems, and improve their overall quality of life.

**Wounds and injuries**refer to any type of damage or harm caused to the body's tissues, bones, or organs, typically resulting from physical trauma.

In the medical field, "wounds and injuries" refer to any type of damage or harm that is inflicted on the body, typically as a result of an external force or trauma. This can include cuts, scrapes, bruises, burns, fractures, and other types of physical trauma. Wounds can be classified based on their depth and severity. Superficial wounds only penetrate the outer layer of skin (epidermis) and are typically easy to treat. Deeper wounds, such as lacerations or punctures, can penetrate the dermis or subcutaneous tissue and may require more extensive medical attention. Injuries can also be classified based on their cause. For example, a fall may result in both a wound (such as a cut or bruise) and an injury (such as a broken bone or concussion). Injuries can be further classified based on their location, severity, and potential long-term effects. The treatment of wounds and injuries typically involves cleaning and dressing the affected area, administering pain medication if necessary, and monitoring for signs of infection or other complications. In some cases, more extensive medical treatment may be required, such as surgery or physical therapy.

Systemic Lupus Erythematosus (SLE) is a chronic autoimmune disorder that affects multiple organs and systems in the body. It is characterized by the production of autoantibodies that attack healthy cells and tissues, leading to inflammation and damage. The symptoms of SLE can vary widely and may include joint pain and swelling, skin rashes, fatigue, fever, and kidney problems. Other possible symptoms may include chest pain, shortness of breath, headaches, and memory problems. SLE can affect people of all ages and ethnicities, but it is more common in women than in men. There is no known cure for SLE, but treatment can help manage symptoms and prevent complications. Treatment may include medications to reduce inflammation, suppress the immune system, and prevent blood clots. In some cases, hospitalization may be necessary to manage severe symptoms or complications.

**Poisoning**is the harmful effect on the body resulting from the intake of a toxic substance.

In the medical field, poisoning refers to the harmful effects that occur when a person is exposed to a toxic substance, either intentionally or unintentionally. Poisoning can occur through ingestion, inhalation, or skin contact with a toxic substance. The effects of poisoning can vary widely depending on the type and amount of the toxic substance, as well as the individual's age, health status, and other factors. Symptoms of poisoning can include nausea, vomiting, diarrhea, abdominal pain, headache, dizziness, confusion, seizures, and even coma or death in severe cases. Treatment for poisoning depends on the type and severity of the exposure. In some cases, supportive care such as fluid replacement, oxygen therapy, or medication to manage symptoms may be necessary. In more severe cases, hospitalization and specialized treatment may be required. Prevention of poisoning is the best approach, and this can involve measures such as proper storage and labeling of toxic substances, avoiding exposure to hazardous materials, and educating individuals about the risks associated with certain substances.

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**statistics**and probability theory, the

**nonparametric**skew is a

**statistic**occasionally used with random variables that take ... The test

**statistic**was T = m − a J . {\displaystyle T={\frac {m-a}{J}}.} The scaled

**statistic**T√n is asymptotically normal with ... Bowley dropped the factor 3 from this formula in 1901 leading to the

**nonparametric**skew

**statistic**. The relationship between the ... When p = q = 0.5 the absolute value of this

**statistic**is bounded by 1. With p = 0.1 and p = 0.01, the

**statistic's**absolute ...

**Nonparametric** regression

**statistics**) Local regression

**Non-parametric**

**statistics**Semiparametric regression Isotonic regression Multivariate ... HyperNiche, software for

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**Nonparametric**regression is a category of regression analysis in which the predictor does not take a predetermined form but is ... In

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###### Friedman test

**Nonparametric**

**Statistics**for the Behavioral Sciences (2nd ed.). New York: McGraw-Hill. ISBN 978-0-07-100326-1. (Articles ... 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- ... Daniel, Wayne W. (1990). "Friedman two-way analysis of variance by ranks". Applied

**Nonparametric**

**Statistics**(2nd ed.). Boston: ...

###### Ranking (**statistics**)

**Nonparametric**

**statistics**). ... In

**statistics**, ranking is the data transformation in which ... In some other cases, descending ranks are used.) Ranks are related to the indexed list of order

**statistics**, which consists of ... By sorting them into order, we have defined their order

**statistics**X n , ( 1 ) ≤ . . . ≤ X n , ( n ) {\displaystyle X_{n,(1)}\ ... Vaart, A. W. van der (1998). Asymptotic

**statistics**. Cambridge, UK: Cambridge University Press. ISBN 9780521784504. ( ...

###### Record value

**Nonparametric**

**statistics**). ... In

**statistics**, a record value or record

**statistic**is the ... The theory is closely related to that used in order

**statistics**. The term was first introduced by K. N. Chandler in 1952. Ladder ... height process MinHash Ahsanullah, Mohammad; Nevzorov, Valery B. (2011). "Record

**Statistics**". International Encyclopedia of ...

###### Kernel smoother

**Nonparametric**

**statistics**). ...

###### Boundary problem (spatial analysis)

**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

**statistics**, the Lepage test is an exact 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 ...

###### Hannu Oja

**Nonparametric**Methods with R. Lecture Notes in

**Statistics**. Vol. 199. New York, NY: Springer New ... Nordhausen, Klaus; Oja, Hannu (2018-03-07). "Robust

**Nonparametric**Inference". Annual Review of

**Statistics**and Its Application. ... Oja, Hannu (1983). "Descriptive

**statistics**for multivariate distributions".

**Statistics**& Probability Letters. 1 (6): 327-332. ... "Descriptive

**statistics**for

**nonparametric**models. The impact of some Erich Lehmann's papers", Selected Works of E. L. Lehmann, ...

###### Charles Joel Stone

**nonparametric**regression". The Annals of

**Statistics**. 5 (4): 595-620. doi:10.1214/aos/ ... Lecture Notes in

**Statistics**, vol. 171. pp. 285-296. ISBN 9780387215792. Hoel, P.; Port, S. C.; Stone, C. J. (1971). ... He was elected a Fellow of the Institute of Mathematical

**Statistics**in 1970 and a Fellow of the Class of 2013 (announced in ... He then matriculated at Stanford University, where in 1961 he received his PhD in

**statistics**. His PhD thesis Limit Theorems for ...

###### Sign test

**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 ...

###### K-nearest neighbors algorithm

**statistics**, the k-nearest neighbors algorithm (k-NN) is a

**non-parametric**supervised learning method first developed by ... 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: ...

###### Mathematical **statistics**

**statistics**,

**nonparametric**

**statistics**make no assumptions about the probability distributions of the variables ...

**Nonparametric**

**statistics**are values calculated from data in a way that is not based on parameterized families of probability ... Upton, G., Cook, I. (2008) Oxford Dictionary of

**Statistics**, OUP. ISBN 978-0-19-954145-4 "Research

**Nonparametric**Methods". ... inferential

**statistics**- the part of

**statistics**that draws conclusions from data (using some model for the data): For example, ...

###### Hodges-Lehmann estimator

**statistics**,

**Nonparametric**

**statistics**). ... 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 ...

###### Empirical likelihood

**statistics**, empirical likelihood (EL) is a

**nonparametric**method for estimating the parameters of ... Journal of

**Nonparametric**

**Statistics**. 22 (2): 237-255. doi:10.1080/10485250903301525. ISSN 1048-5252. S2CID 119684596. Chen, ... Empirical likelihood can naturally be applied in survival analysis or regression problems Bootstrapping (

**statistics**) Jackknife ... The Annals of

**Statistics**. 18 (1). doi:10.1214/aos/1176347494. ISSN 0090-5364. Dong, Lauren Bin; Giles, David E. A. (2007-01-30 ...

###### Wald-Wolfowitz runs test

**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. ...

###### Delta method

**Nonparametric**

**Statistics**. New York: Springer. pp. 19-20. ISBN 0-387-25145-6 ... A version of the delta method exists in

**nonparametric**

**statistics**. Let X i ∼ F {\displaystyle X_{i}\sim F} be an independent and ... In

**statistics**, the delta method is a result concerning the approximate probability distribution for a function of an ... ISBN 978-1-4338-0048-1. Doob, J. L. (1935). "The Limiting Distributions of Certain

**Statistics**". Annals of Mathematical ...

###### Functional principal component analysis

**Nonparametric**

**statistics**). ... Staniswalis, J. G.; Lee, J. J. (1998). "

**Nonparametric**Regression Analysis of Longitudinal Data". Journal of the American ... Li, Y.; Hsing, T. (2010). "Uniform convergence rates for

**nonparametric**regression and principal component analysis in ... The Annals of

**Statistics**. 33 (6): 2873. arXiv:math/0603132. doi:10.1214/009053605000000660. Yao, F.; Müller, H. G.; Wang, J. L ...

###### Bretagnolle-Huber inequality

**nonparametric**estimation. Springer Series in

**Statistics**. Springer. doi:10.1007/ ... It is used in

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###### Cucconi test

**statistics**, the Cucconi test is a

**nonparametric**test for jointly comparing central tendency and variability (detecting ... Marozzi, Marco (2009). "Some Notes on the Location-Scale Cucconi Test". Journal of

**Nonparametric**

**Statistics**. 21 (5): 629-647. ... Articles with short description, Short description matches Wikidata,

**Nonparametric**

**statistics**). ... 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}}={\ ...

###### Kruskal-Wallis one-way analysis of variance

**statistic**". Journal of

**Nonparametric**

**Statistics**. 15 (6 ... Siegel; Castellan (1988).

**Nonparametric**

**Statistics**for the Behavioral Sciences (Second ed.). New York: McGraw-Hill. ISBN ... Corder, Gregory W.; Foreman, Dale I. (2009).

**Nonparametric**

**Statistics**for Non-Statisticians. Hoboken: John Wiley & Sons. pp. 99 ... Applied

**Nonparametric**

**Statistics**(2nd ed.). Boston: PWS-Kent. pp. 226-234. ISBN 0-534-91976-6. An online version of the test ( ...

###### Stein's unbiased risk estimate

**Nonparametric**

**Statistics**. (Point estimation performance). ... In

**statistics**, Stein's unbiased risk estimate (SURE) is an unbiased estimator of the mean-squared error of "a nearly arbitrary ... Stein, Charles M. (November 1981). "Estimation of the Mean of a Multivariate Normal Distribution". The Annals of

**Statistics**. 9 ...

###### Phillip Good

**Nonparametric**

**Statistics**. 1 (3): 253- ... Common Errors in

**Statistics**(and How to Avoid Them) (with J. Hardin), Wiley, 2003 (4th edition, 2012). Applying

**Statistics**in ... Introduction to

**Statistics**Using Resampling Methods and R/S-Plus. Wiley, 2005 (2nd edition, 2012). Introduction to

**Statistics**... His chief contributions to

**statistics**are in the area of small sample

**statistics**, including a uniformly most powerful unbiased ...

###### Analysis of variance

**nonparametric**statistical methods. Kendall's Library of

**Statistics**. Vol. 5 (First ed.). New York: John Wiley & Sons, Inc ... 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

**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**. Vol. 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

**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- ...

###### Mann-Whitney U test

**Nonparametric**

**statistics**for the behavioral sciences. McGraw-Hill. p. 121. Lehmann, Erich; D'Abrera, ... MATLAB has ranksum in its

**Statistics**Toolbox. R's

**statistics**base-package implements the test wilcox.test in its "

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

**Nonparametric**

**Statistics**: A Step-by-Step Approach. Wiley. ISBN 978-1118840313. Hodges, J.L ... Conover, William J.; Iman, Ronald L. (1981). "Rank Transformations as a Bridge Between Parametric and

**Nonparametric**

**Statistics**...

###### Tukey-Duckworth test

**Nonparametric**

**statistics**). ... In

**statistics**, the Tukey-Duckworth test is a two-sample ...

###### Pinsker's inequality

**Statistics**. Springer, New York, 2009. xii+214 pp. ISBN 978-0-387-79051-0, Equation 2.25. Tsybakov, Alexandre ... Introduction to

**nonparametric**estimation, Revised and extended from the 2004 French original. Translated by Vladimir Zaiats. ... 2009). Introduction to

**Nonparametric**Estimation. Springer. p. 132. ISBN 9780387790527. The divergence becomes infinite whenever ...

**Nonparametric** **statistics** | Radiology Reference Article | Radiopaedia.org

**Nonparametric**

**statistics**is the area of

**statistics**that deals with data which either does not have a probability distribution ...

**Nonparametric**

**statistics**. Last revised by Candace Makeda Moore ◉ on 10 Sep 2020 ...

**Nonparametric**tests are often practically very useful when a data sets distribution is unknown e.g. when testing the ... Moore C,

**Nonparametric**

**statistics**. Reference article, Radiopaedia.org (Accessed on 21 Sep 2023) https://doi.org/10.53347/rID- ...

###### Advanced **Statistics** in Education and Psychology: Parametric and **Nonparametric** > Sharma, R.A. | Saujanya...

###### Details for:
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**Nonparametric**

**statistics**for the behavioral sciences / HA 29 63HO

**Statistics**for medical students / HA 29 67BU ...

**Nonparametric**

**statistics**for the behavioral sciences / Sidney Siegel. By: Siegel, SidneyMaterial type: TextPublication details ... HA 29 53CR Elementary

**statistics**with applications in medicine / ... Details for:

**Nonparametric**

**statistics**for the behavioral ... New York : McGraw-Hill, 1956. Description: 312 pSubject(s): StatisticsNLM classification: HA 29 ...

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###### EconPapers: Differences of opinion and stock market volatility: evidence from a **nonparametric** causality-in-quantiles approach

**Statistics**for this article. Journal of Economics and Finance is currently edited by James Payne More articles in ... Differences of opinion and stock market volatility: evidence from a

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**statistics**for the culture analysis of the dry and wet swab, wipe, and HEPA vacuum sock samples are shown in Table ...

**Nonparametric**statistical methods. 2nd edition. New York: John Wiley & Sons, Inc.; 1999. p. 394-408. ... Sample summary

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**Non-parametric**Physiological Classification of Retinal Ganglion Cells in the Mouse Retina. Jonathan Jouty1 Gerrit Hilgen2 ... Tibshirani, R., Walther, G., and Hastie, T. (2001). Estimating the number of clusters in a data set via the gap

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###### E. Scott Mayfield - Faculty & Research - Harvard Business School

**Statistics**10, no. 3 (July 1992). ... "

**Nonparametric**Estimation of the Correlation Exponent." Physical Review, A (1991). View Details ... "On Determining the Dimension of Real-Time Stock Price Data." Journal of Business & Economic

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###### Publications and Software

**Statistics**, to appear.. * Wang, H., Peng, B., Li, D., and Leng, C. (2020).

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**Statistics**and Its Interface, 8, 255-266.. *Zhang, W., Leng, C., and Tang, C. Y. (2015). A joint modeling approach for ... The Annals of

**Statistics**, 41, 2639-2667.. *Leng, C. and Tong, X. (2013). A quantile regression estimator for censored data ( ... Journal of Computational and Graphical

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###### Quantities in Probability & **Statistics**: New in Wolfram Language 11

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###### The Effects of Visual Stimulation and Selective Visual Attention on Rhythmic Neuronal Synchronization in Macaque Area V4 |...

**nonparametric**randomization

**statistic**, correcting for multiple comparisons across time). The format is the same as in A, but ... We then calculated the test

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###### Managerial efficiency and efficiency differentials in adult education: a conditional and bias-corrected efficiency analysis |...

**nonparametric**plots are equivalent to Fig. 4 (see Figs. 5, 6, 7 in the "Appendix") when running the second stage ... Summary

**statistics**on the number of sessions per program and the number of learners per program are provided in Table 1. ... We do so in a

**nonparametric**manner as a linear, a parabolic, or even a Fourier relationship (Schiltz and De Witte 2017) might ... The first panel of Table 1 reports summary

**statistics**for the input and the outputs. As an input, we consider the cost per ...

###### DFISimilarity (Lucene 6.0.0 API)

**stats**. - the corpus level

**statistics**.. freq. - the term frequency.. docLen. - the document length.. Returns:. the score.. ... DFI is both parameter-free and

**non-parametric**: *parameter-free: it does not require any parameter tuning or training. ...

**non-parametric**: it does not make any assumptions about word frequency distributions on document collections. ... Implements the Divergence from Independence (DFI) model based on Chi-square

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###### La resiliencia modera la asociación entre los episodios anímicos del trastorno bipolar y la salud mental

###### Advanced Introduction to Spatial **Statistics**

**statistics**. I ...

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###### Biochemistry | Middle Tennessee State University

**Statistics**for Analytical Chemistry 3 credit hours Prerequisite: CHEM 2230/CHEM 2231 or CHEM 4330/ ... Propogation of error, linear regression, ANOVA, non-linear regression, and

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###### Parametric2

- Nonparametric tests are often practically very useful when a data set's distribution is unknown e.g. when testing the correlation between two variables for a regression, it is often inappropriate to assume the variables studied are normally distributed, and therefore a Pearson's correlation is inappropriate and the Spearman rank correlation would be the non-parametric test that could be applied to such data. (radiopaedia.org)
- Advanced EEG analysis using threshold-free cluster-enhancement and non-parametric statistics. (crossref.org)

###### Estimation5

- The motions improved for download Introduction to Nonparametric Estimation (Springer Series in Statistics) cardsBusiness must halt outer to include the cyclophilin oxidized by metastable world" to the laser protein. (robertfischer.name)
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- Nonparametric Estimation of the Correlation Exponent. (hbs.edu)
- Nonparametric estimation of large covariance matrices with conditional sparsity. (warwick.ac.uk)

###### Bayesian1

- Bayesian nonparametric clustering in phylogenetics: modeling antigenic evolution in influenza. (cdc.gov)

###### 20201

- Participaron 520 jóvenes: 246 estudiantes de bachillerato y universidad en el año 2020, durante el confinamiento y 274, search, writing, revision and en 2022. (bvsalud.org)

###### Statistical3

- Discussion of 'Statistical modelling of citation exchange between statistics journals' by Varin, Cattelan and Firth, Journal of the Royal Statistical Society Series A, 179, 54. (warwick.ac.uk)
- It offers a vital tool for understanding spatial statistics and surveys how concerns about violating the independent observations assumption of statistical analysis developed into this discipline. (e-elgar.com)
- In most nonparametric statistical tests, the original scores or observations are replaced by another variable containing less information. (bvsalud.org)

###### Spatial Statistics4

- This Advanced Introduction provides a critical review and discussion of research concerning spatial statistics, differentiating between it and spatial econometrics, to answer a set of core questions covering the geographic-tagging-of-data origins of the concept and its theoretical underpinnings, conceptual advances, and challenges for future scholarly work. (e-elgar.com)
- The helpful insights from empirical applications of spatial statistics in agronomy, criminology, demography, economics, epidemiology, geography, remotely sensed data, urban studies, and zoology/botany, will make this book a useful tool for upper-level students in these disciplines. (e-elgar.com)
- With widespread and increasingly available georeferenced data, this book offers a timely assessment of contemporary methods, models, and metrics-such as the eigenvector spatial filtering approach to handling spatial autocorrelation-in spatial statistics. (e-elgar.com)
- An advanced introduction to spatial statistics: motivation and scope 2. (e-elgar.com)

###### Descriptive statistics2

- Support for quantities in descriptive statistics. (wolfram.com)
- Descriptive statistics, data visualisation. (muni.cz)

###### Independence1

- Implements the Divergence from Independence (DFI) model based on Chi-square statistics (i.e., standardized Chi-squared distance from independence in term frequency tf). (apache.org)

###### Data4

- Nonparametric statistics is the area of statistics that deals with data which either does not have a probability distribution or that does not have the distribution's parameters specified. (radiopaedia.org)
- Version 11 supports quantities across the probability and statistics functionality, fully automating conversion, propagation, and transformations - from data to models to correct interpretation. (wolfram.com)
- Use quantity data to build nonparametric distributions. (wolfram.com)
- An important class of nonparametric tests employs the ordinal properties of the data. (bvsalud.org)

###### Economics1

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###### Test2

- Abstract This paper examines whether the differences of opinion across active money managers relates to stock market volatility via the recently proposed nonparametric causality-in-quantiles test. (repec.org)
- Unlike the result of no predictability obtained under the misspecified linear set-up, our nonparametric causality-in-quantiles test indicates that dispersion in active managers' risk exposures to the stock market can predict volatility over the range of quantiles that correspond to moderately high levels of market volatility. (repec.org)

###### Journal2

- Journal of Business & Economic Statistics 10, no. 3 (July 1992). (hbs.edu)
- Journal of Business and Economic Statistics, to appear. (warwick.ac.uk)

###### Introduction1

- Introduction to statistics, testing of hypotheses. (muni.cz)

###### University1

- Francesca obtained her PhD in Statistics at the University of Oxford in 2022. (lse.ac.uk)

###### Parametric statistics2

- Unlike = parametric statistics, nonparametric statistics make no assumptions about t= he probability distributions of the variables being assessed. (nylxs.com)
- In one-sample tests, combination of contrast estimates into a random-effects General Linear Model or non-parametric statistics provide a good approximation of the reference approach. (biorxiv.org)

###### Regression8

- Nonparametric regression analysis of data from the Ames mutagenicity assay. (nih.gov)
- We study yet another approach, the application of nonparametric regression techniques, not as the ultimate solution but rather as a framework within which to address some of the shortcomings of other methods. (nih.gov)
- But nonparametric regression is itself prone to difficulties when applied to Ames assay data, as we show through the use of two examples and some simulation studies. (nih.gov)
- We compare the performance of TDI using nonparametric quantile regression to the TDI assuming normality (Lin, 2000). (nih.gov)
- Monotone nonparametric regression and confidence intervals. (nih.gov)
- An introduction to the basic ideas and techniques of probability theory and to selected topics in statistics, such as sampling theory, confidence intervals, and linear regression. (juniata.edu)
- Introduction to traditional statistical concepts including descriptive statistics, binomial and normal probability models, confidence intervals, tests of hypotheses, linear correlation and regression, two-way contingency tables, and one-way analysis of variance. (juniata.edu)
- This course covers basic descriptive and inferential statistics, normal curve and z-score computations, and addresses hypothesis testing using Chi-Square, T-Test, ANOVA, and linear regression modelling. (juniata.edu)

###### Probability2

- He was Editor of Biometrika (2008-2017), Joint Editor of Journal of the Royal Statistical Society, series B (2000-2003), editor of the IMS Lecture Notes Monograph Series (2007), Associate Editor of Biometrika (1987-1999), and Associate Editor of the Brazilian Journal of Probability and Statistics (1987 2006). (epfl.ch)
- Nonparametric statistics are statistics not based on parameterized famili= es of probability distributions. (nylxs.com)

###### Methods4

- His main research interests are statistics of extremes, likelihood asymptotics, bootstrap and other resampling methods, and statistical modelling, with a particular focus on the first currently. (epfl.ch)
- She developed nonparametric and semiparametric methods to simultaneously analyze multiple time-to-event outcomes, to facilitate risk assessment of multiple diseases across individual's lifespan. (nih.gov)
- This course offers an in-depth exploration of the fundamental principles in statistics and the primary methods employed to identify and measure disease and associated risks. (birmingham.ac.uk)
- This short course provides an introduction to the basic concepts in statistics and the main epidemiological methods used to identify and quantify disease and associated risks. (birmingham.ac.uk)

###### Computational Statistics1

- Computational Statistics & Data Analysis , 89:1-11, 2015. (nih.gov)

###### Mathematics3

- Restriction B: Not open to students who have taken or are taking MATH 123 , except by permission of the Department of Mathematics and Statistics. (mcgill.ca)
- Mathematics & Statistics (Sci) : Review of functions and graphs. (mcgill.ca)
- Mathematics & Statistics (Sci) : The definite integral. (mcgill.ca)

###### Analysis1

- When image data is available for each study, a number of approaches have been proposed to perform such meta-analysis including combination of standardised statistics, just effect estimates or both effects estimates and their sampling variance. (biorxiv.org)

###### Principles1

- This course introduces the student to the emerging field of data science through the presentation of basic math and statistics principles, an introduction to the computer tools and software commonly used to perform the data analytics, and a general overview of the machine learning techniques commonly applied to datasets for knowledge discovery. (juniata.edu)

###### Research1

- We want to conduct some meaningful and fruitful research into multivariate nonparametric econometrics. (cas.cz)

###### Provide1

- Moreover, by focusing on excess risk rather than parameter estimation, we can provide rates under weaker assumptions than in previous works and accommodate settings in which the target parameter belongs to a complex nonparametric class. (projecteuclid.org)

###### Approach1

- I tried using Montecarlo simulations, however I am not sure whether this is the correct approach, since my statistics where non-parametric. (nih.gov)

###### Fellow1

- He is an elected Fellow of the American Statistical Assocation and of the Institute of Mathematical Statistics, an elected member of the International Statistical Institute, and a Chartered Statistician. (epfl.ch)

###### Medicine2

###### Applications1

- Currently he on the editorial board of Annual Reviews of Statistics and its Applications. (epfl.ch)

###### Communications1

- Communications in Statistics-Simulation and Computation ® , 39(4):828-845, 2010. (nih.gov)

###### Institute2

###### Include1

- They include both descriptive and inferent= ial statistics. (nylxs.com)