Data Interpretation, Statistical: Application of statistical procedures to analyze specific observed or assumed facts from a particular study.Plant Bark: The outer layer of the woody parts of plants.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.Software: Sequential operating programs and data which instruct the functioning of a digital computer.Oligonucleotide Array Sequence Analysis: Hybridization of a nucleic acid sample to a very large set of OLIGONUCLEOTIDE PROBES, which have been attached individually in columns and rows to a solid support, to determine a BASE SEQUENCE, or to detect variations in a gene sequence, GENE EXPRESSION, or for GENE MAPPING.Algorithms: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.Computer Simulation: Computer-based representation of physical systems and phenomena such as chemical processes.Gene Expression Profiling: The determination of the pattern of genes expressed at the level of GENETIC TRANSCRIPTION, under specific circumstances or in a specific cell.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.Sequence Analysis, DNA: A multistage process that includes cloning, physical mapping, subcloning, determination of the DNA SEQUENCE, and information analysis.Polymerase Chain Reaction: In vitro method for producing large amounts of specific DNA or RNA fragments of defined length and sequence from small amounts of short oligonucleotide flanking sequences (primers). The essential steps include thermal denaturation of the double-stranded target molecules, annealing of the primers to their complementary sequences, and extension of the annealed primers by enzymatic synthesis with DNA polymerase. The reaction is efficient, specific, and extremely sensitive. Uses for the reaction include disease diagnosis, detection of difficult-to-isolate pathogens, mutation analysis, genetic testing, DNA sequencing, and analyzing evolutionary relationships.Sensitivity and Specificity: Binary classification measures to assess test results. Sensitivity or recall rate is the proportion of true positives. Specificity is the probability of correctly determining the absence of a condition. (From Last, Dictionary of Epidemiology, 2d 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).Image Interpretation, Computer-Assisted: Methods developed to aid in the interpretation of ultrasound, radiographic images, etc., for diagnosis of disease.Radiology: A specialty concerned with the use of x-ray and other forms of radiant energy in the diagnosis and treatment of disease.Time Factors: Elements of limited time intervals, contributing to particular results or situations.Diagnostic Errors: Incorrect diagnoses after clinical examination or technical diagnostic procedures.Models, Biological: Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.

*  The importance of statistical evaluation and experimental-design in the interpretation of data from cancer microdetector...

The importance of statistical evaluation and experimental-design in the interpretation of data from cancer microdetector ... This article discusses the importance of statistical evaluation and experimental-design in the interpretation of data from ... The importance of statistical evaluation and experimental-design in the interpretation of data from cancer microdetector ... statistical evaluation, experimental design, cancer microdetector, Probabilities. Mathematical statistics, Neoplasms. Tumors. ...

*  business statistic expert needed for Data Visualisation and Interpretation, Basic Probability and Discrete Probability...

Data Visualisation and Interpretation, Basic Probability and Discrete Probability Distributions Need to answer 3 big questions ... data analysis excel expert needed, business statistic, data entry expert needed, business expert needed, statistic solve ... business statistic expert needed for Data Visualisation and Interpretation, Basic Probability and Discrete Probability ... business statistic expert needed for Data Visualisation and Interpretation, Basic Probability and Discrete Probability ...

*  Volume 3, Issue 1, January 2008: Knowledge Translation and Systematic Reviews | National Rehabilitation Information Center

Data Collection. *Data Interpretation, Statistical. *Decision Making. *Decision Support Techniques. *Dissemination. *Education/ ... The data collection has started in August 2006 and the results will be published independently of the study's outcome. TRIAL ... We describe a Health Canada-funded randomized trial in which quantitative and qualitative data will be gathered in 20 general ... National Spinal Cord Injury Statistical Center (NSCISC). Project Number: H133A060039. ...

*  Postmortem lung weight in drownings: a comparison with acute asphyxiation and cardiac death.

Data Interpretation, Statistical. Drowning / diagnosis*, pathology. Female. Fresh Water. Heart Arrest / diagnosis*, pathology. ...

*  Free-knot spline model for analysis of pulmonary function.

Data Interpretation, Statistical. Databases, Factual. Forced Expiratory Volume*. Humans. Lung / physiology*. Middle Aged. ...

*  Subject order-independent group ICA (SOI-GICA) for functional MRI data analysis.

... data. Particularly, for group analysis on multiple subjects, temporally concatenation group ICA (TC-GICA) is intensively used. ... is a data-driven approach to study functional magnetic resonance imaging (fMRI) ... Data Interpretation, Statistical. Executive Function / physiology. Female. Humans. Image Processing, Computer-Assisted. ... To overcome this, TC-GICA employs multiple-stage PCA data reduction. Such multiple-stage PCA data reduction, however, leads to ...

*  Cerebral tissue oxygen saturation calculated using low frequency haemoglobin oscillations measured by near infrared...

Data Interpretation, Statistical. Fourier Analysis. Hemoglobins / metabolism*. Humans. Oximetry / methods. Oxygen / blood*. ...

*  Variance matters: the shape of a datum.

... choice data are most often plotted and analyzed as logarithmic transforms of ratios of responses and of ratios of reinforcers ... Data Interpretation, Statistical*. Discrimination (Psychology) / physiology. Humans. Models, Psychological*. Models, ... However, linear regression of this type requires that the log choice data be normally distributed, of equal variance for each ... In the quantitative analysis of behaviour, choice data are most often plotted and analyzed as logarithmic transforms of ratios ...

*  Evaluating qualitative assays using sensitivity and specificity.

Data Interpretation, Statistical. Humans. Laboratory Techniques and Procedures / statistics & numerical data. Sample Size. ... Biological Assay / statistics & numerical data*. Blood Chemical Analysis / statistics & numerical data. Computer Simulation. ... 24737796 - The quality of police data on rtc fatalities in india.. 21077176 - A method to calculate the volume of palatine ...

*  Exact sample size needed to detect dependence in 2 x 2 x 2 tables.

Data Interpretation, Statistical*. Georgia / epidemiology. Humans. Longevity / genetics*. Markov Chains. Models, Genetic*. ...

*  Randomized trials published in higher vs. lower impact journals differ in design, conduct, and analysis.

Data Interpretation, Statistical. Humans. Journal Impact Factor*. Periodicals as Topic / standards*, statistics & numerical ... Previous Document: The validity of administrative data to identify hip fractures is high-a systematic review.. Next Document: ... data. Randomized Controlled Trials as Topic / methods, standards*. Research Design / standards. Sample Size. ...

*  Leadership Studies - Bradley University

ENC 510 - Statistical Procedures (3 hours) Principles and procedures for statistical interpretation of data. Study of measures ... ENC 310 - Statistical Procedures in Health Sciences (3 hours) Principles and procedures for statistical interpretation of data ... Statistical concepts and social/cultural factors related to assessment and evaluation.. ENC 651 - Clinical Mental Health ... Research methods, statistical analysis, needs assessment, and program evaluation utilized in counseling, education, and human ...

*  Wiley: Research Methods in Clinical Linguistics and Phonetics: A Practical Guide - Nicole Muller, Martin J. Ball

13 Data Processing: Imaging of Speech Data 219. Joan Rahilly. 14 Data Analysis and Interpretation: Statistical Methods 253. ... 11 Data Processing: Transcriptional and Impressionistic Methods 177. Martin J. Ball, Sara Howard, Nicole Müller, and Angela ... 15 AphasiaBank: Data and Methods 268. Brian MacWhinney, Davida Fromm, Audrey Holland, and Margaret Forbes ... 10 The Recording of Audio and Video Data 160. Ben Rutter and Stuart Cunningham ...

*  Full text of "Ivy Tech State College Central Indiana Region Bulletin, 1994-1995"

Stresses interpretation of statistical data and distinguishing between common and special causes of problems. Emphasizes ... Covers various equipment, techniques of data collection, interpretation and evaluation of data used in monitoring the ... Studies arterial blood gas collection, analysis and interpretation, and basic medical laboratory data. Introduces concepts and ... QSC 102 Statistical Process Control 3 Credits Studies the fundamental tools of statistical process control which are used in ...

*  Statistical Modeler Jobs, Employment in Jacksonville, FL |

Statistical Modeler Jobs available in Jacksonville, FL on one search. all jobs. ... Statistical data analysis and interpretation; Performance of statistical analyses on collected data and simulated results;... ... Statistical Modeler jobs in Jacksonville, FL. Filter results by: Sort by: relevance - date ... Be the first to see new Statistical Modeler jobs in Jacksonville, FL ...,-FL-jobs.html

*  Applied Social Research (SOCS2400) / Course / The University of Newcastle, Australia

interpretation of numerical and statistical data.. Assumed knowledge. 40 units of study at 1000 level. ... and interpretation of numerical data. The computer workshops will include an introduction to appropriate software packages such ... This course concentrates on the collection and analysis of quantitative data and the reporting of results. Students develop an ... The course does not require previous statistical knowledge.. Availability2017 Course Timetables. Callaghan. *Semester 2 - 2017 ...

*  Books - Medicine - Terkko Navigator

DNA microarray technology and data analysis in cancer research. Cancer cells, DNA microarrays, Data Interpretation, Statistical ...

*  Undergraduate | Programme Specifications | Loughborough University

Understanding of the appropriate techniques to enable manipulation, treatment and interpretation of relevant statistical data. ... Data, and their effective organization, presentation and analysis, are important in economics. The typical student will have ... Students will have exposure to the use of such techniques on actual economic, financial or social data. A knowledge and ... Understanding of relevant mathematical and statistical techniques.. *Understanding of analytical methods, both theory- and ...

*  No study left behind: a network meta-analysis in non-small-cell lung cancer demonstrating the importance of considering all...

Data Interpretation, Statistical; Erlotinib Hydrochloride; Female; Humans; Lung Neoplasms /drug therapy; Male; Middle Aged; ... Data extraction. The number of events for each outcome was extracted in order to calculate hazard ratios (HR) and 95% ... Research: The authors identified a need for further work using regression analysis of both study and individual level data in ... All potentially relevant data should be considered when comparing treatments. Erlotinib, docetaxel and gefitinib were ...

*  New Print Books for January « UT Health Science Center Library

Data Interpretation, Statistical. Applied medical statistics using SAS / Geoff Der, Brian S. Everitt.. Boca Raton, Fla. : CRC ...

*  Based on the yeast interaction data of Duan et al., hyp | Open-i

Based on the yeast interaction data of Duan et al., hypergeometric and resampling-based P-values were computed to assess the ... Data Interpretation, Statistical. *Gene Expression Regulation, Fungal. *Genes, Fungal. *Genome, Fungal. *Statistics, ... gks012-F2: Based on the yeast interaction data of Duan et al., hypergeometric and resampling-based P-values were computed to ... gks012-F2: Based on the yeast interaction data of Duan et al., hypergeometric and resampling-based P-values were computed to ...

*  Treatment and control observed means and variances and | Open-i

Bottom Line: A common interest in gene expression data analysis is to identify from a large pool of candidate genes the genes ... Usually, it is done using a statistic value and a cutoff value that are used to separate the genes differentially and ... Bottom Line: A common interest in gene expression data analysis is to identify from a large pool of candidate genes the genes ... A common interest in gene expression data analysis is to identify from a large pool of candidate genes the genes that present ...

*  Long-term Relationship of Ovulation-Stimulating Drugs to Breast Cancer Risk | Cancer Epidemiology, Biomarkers & Prevention

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): L.A. Brinton, B. ... Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): L.A. Brinton, B. Scoccia, K.S ... Cancer incidence data have been provided by the following cancer registries and/or state departments of health: Arizona Cancer ... Statistical analyses. HRs and 95% confidence intervals (CI) for breast cancer associated with fertility treatments, with ...

*  Plus it

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): J.-D. Combes, A.A. ... The main weakness of our study lies in the fact that there is limited or no country-specific data on HPV prevalence in OPC and ... When HPV prevalence data were applied to age-standardized OPC incidence rates in the United States, Australia, the United ... Because of limited data available, findings from mRNA and ISH were combined (hereafter referred together as mRNA/ISH). ...

Carl Barks: "United States Social Security Death Index," index, FamilySearch ( theory: Generalizability theory, or G Theory, is a statistical framework for conceptualizing, investigating, and designing reliable observations. It is used to determine the reliability (i.Mac OS X Server 1.0Cellular microarray: A cellular microarray is a laboratory tool that allows for the multiplex interrogation of living cells on the surface of a solid support. The support, sometimes called a "chip", is spotted with varying materials, such as antibodies, proteins, or lipids, which can interact with the cells, leading to their capture on specific spots.Clonal Selection Algorithm: In artificial immune systems, Clonal selection algorithms are a class of algorithms inspired by the clonal selection theory of acquired immunity that explains how B and T lymphocytes improve their response to antigens over time called affinity maturation. These algorithms focus on the Darwinian attributes of the theory where selection is inspired by the affinity of antigen-antibody interactions, reproduction is inspired by cell division, and variation is inspired by somatic hypermutation.Interval boundary element method: Interval boundary element method is classical boundary element method with the interval parameters.
Gene signature: A gene signature is a group of genes in a cell whose combined expression patternItadani H, Mizuarai S, Kotani H. Can systems biology understand pathway activation?PSI Protein Classifier: PSI Protein Classifier is a program generalizing the results of both successive and independent iterations of the PSI-BLAST program. PSI Protein Classifier determines belonging of the found by PSI-BLAST proteins to the known families.DNA sequencer: A DNA sequencer is a scientific instrument used to automate the DNA sequencing process. Given a sample of DNA, a DNA sequencer is used to determine the order of the four bases: G (guanine), C (cytosine), A (adenine) and T (thymine).Thermal cyclerAssay sensitivity: Assay sensitivity is a property of a clinical trial defined as the ability of a trial to distinguish an effective treatment from a less effective or ineffective intervention. Without assay sensitivity, a trial is not internally valid and is not capable of comparing the efficacy of two interventions.Thomas KolbTemporal analysis of products: Temporal Analysis of Products (TAP), (TAP-2), (TAP-3) is an experimental technique for studyingPrescription cascade: Prescription cascade refers to the process whereby the side effects of drugs are misdiagnosed as symptoms of another problem resulting in further prescriptions and further side effects and unanticipated drug interactions. This may lead to further misdiagnoses and further symptoms.Matrix model: == Mathematics and physics ==

(1/9497) A method for calculating age-weighted death proportions for comparison purposes.

OBJECTIVE: To introduce a method for calculating age-weighted death proportions (wDP) for comparison purposes. MATERIALS AND METHODS: A methodological study using secondary data from the municipality of Sao Paulo, Brazil (1980-1994) was carried out. First, deaths are weighted in terms of years of potential life lost before the age of 100 years. Then, in order to eliminate distortion of comparisons among proportions of years of potential life lost before the age of 100 years (pYPLL-100), the denominator is set to that of a standard age distribution of deaths for all causes. Conventional death proportions (DP), pYPLL-100, and wDP were calculated. RESULTS: Populations in which deaths from a particular cause occur at older ages exhibit lower wDP than those in which deaths occur at younger ages. The sum of all cause-specific wDP equals one only when the test population has exactly the same age distribution of deaths for all causes as that of the standard population. CONCLUSION: Age-weighted death proportions improve the information given by conventional DP, and are strongly recommended for comparison purposes.  (+info)

(2/9497) A review of statistical methods for estimating the risk of vertical human immunodeficiency virus transmission.

BACKGROUND: Estimation of the risk of vertical transmission of human immunodeficiency virus (HIV) has been complicated by the lack of a reliable diagnostic test for paediatric HIV infection. METHODS: A literature search was conducted to identify all statistical methods that have been used to estimate HIV vertical transmission risk. Although the focus of this article is the analysis of birth cohort studies, ad hoc studies are also reviewed. CONCLUSIONS: The standard method for estimating HIV vertical transmission risk is biased and inefficient. Various alternative analytical approaches have been proposed but all involve simplifying assumptions and some are difficult to implement. However, early diagnosis/exclusion of infection is now possible because of improvements in polymerase chain reaction technology and complex estimation methods should no longer be required. The best way to analyse studies conducted in breastfeeding populations is still unclear and deserves attention in view of the many intervention studies being planned or conducted in developing countries.  (+info)

(3/9497) Statistical inference by confidence intervals: issues of interpretation and utilization.

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)

(4/9497) Incidence and duration of hospitalizations among persons with AIDS: an event history approach.

OBJECTIVE: To analyze hospitalization patterns of persons with AIDS (PWAs) in a multi-state/multi-episode continuous time duration framework. DATA SOURCES: PWAs on Medicaid identified through a match between the state's AIDS Registry and Medicaid eligibility files; hospital admission and discharge dates identified through Medicaid claims. STUDY DESIGN: Using a Weibull event history framework, we model the hazard of transition between hospitalized and community spells, incorporating the competing risk of death in each of these states. Simulations are used to translate these parameters into readily interpretable estimates of length of stay, the probability that a hospitalization will end in death, and the probability that a nonhospitalized person will be hospitalized within 90 days. PRINCIPAL FINDINGS: In multivariate analyses, participation in a Medicaid waiver program offering case management and home care was associated with hospital stays 1.3 days shorter than for nonparticipants. African American race and Hispanic ethnicity were associated with hospital stays 1.2 days and 1.0 day longer than for non-Hispanic whites; African Americans also experienced more frequent hospital admissions. Residents of the high-HIV-prevalence area of the state had more frequent admissions and stays two days longer than those residing elsewhere in the state. Older PWAs experienced less frequent hospital admissions but longer stays, with hospitalizations of 55-year-olds lasting 8.25 days longer than those of 25-year-olds. CONCLUSIONS: Much socioeconomic and geographic variability exists both in the incidence and in the duration of hospitalization among persons with AIDS in New Jersey. Event history analysis provides a useful statistical framework for analysis of these variations, deals appropriately with data in which duration of observation varies from individual to individual, and permits the competing risk of death to be incorporated into the model. Transition models of this type have broad applicability in modeling the risk and duration of hospitalization in chronic illnesses.  (+info)

(5/9497) Quantitative study of the variability of hepatic iron concentrations.

BACKGROUND: The hepatic iron concentration (HIC) is widely used in clinical practice and in research; however, data on the variability of HIC among biopsy sites are limited. One aim of the present study was to determine the variability of HIC within both healthy and cirrhotic livers. METHODS: Using colorimetric methods, we determined HIC in multiple large (microtome) and small (biopsy-sized) paraffin-embedded samples in 11 resected livers with end-stage cirrhosis. HIC was also measured in multiple fresh samples taken within 5 mm of each other ("local" samples) and taken at sites 3-5 cm apart ("remote" samples) from six livers with end-stage cirrhosis and two healthy autopsy livers. RESULTS: The within-organ SD of HIC was 13-1553 microg/g (CV, 3.6-55%) for microtome samples and 60-2851 microg/g (CV, 15-73%) for biopsy-sized samples. High variability of HIC was associated with mild to moderate iron overload, because the HIC SD increased with increasing mean HIC (P <0.002). Livers with mean HIC >1000 microg/g exhibited significant biological variability in HIC between sites separated by 3-5 cm (remote sites; P <0.05). The SD was larger for biopsy-sized samples than for microtome samples (P = 0.02). CONCLUSION: Ideally, multiple hepatic sites would be sampled to obtain a representative mean HIC.  (+info)

(6/9497) A simulation study of confounding in generalized linear models for air pollution epidemiology.

Confounding between the model covariates and causal variables (which may or may not be included as model covariates) is a well-known problem in regression models used in air pollution epidemiology. This problem is usually acknowledged but hardly ever investigated, especially in the context of generalized linear models. Using synthetic data sets, the present study shows how model overfit, underfit, and misfit in the presence of correlated causal variables in a Poisson regression model affect the estimated coefficients of the covariates and their confidence levels. The study also shows how this effect changes with the ranges of the covariates and the sample size. There is qualitative agreement between these study results and the corresponding expressions in the large-sample limit for the ordinary linear models. Confounding of covariates in an overfitted model (with covariates encompassing more than just the causal variables) does not bias the estimated coefficients but reduces their significance. The effect of model underfit (with some causal variables excluded as covariates) or misfit (with covariates encompassing only noncausal variables), on the other hand, leads to not only erroneous estimated coefficients, but a misguided confidence, represented by large t-values, that the estimated coefficients are significant. The results of this study indicate that models which use only one or two air quality variables, such as particulate matter [less than and equal to] 10 microm and sulfur dioxide, are probably unreliable, and that models containing several correlated and toxic or potentially toxic air quality variables should also be investigated in order to minimize the situation of model underfit or misfit.  (+info)

(7/9497) Wavelet transform to quantify heart rate variability and to assess its instantaneous changes.

Heart rate variability is a recognized parameter for assessing autonomous nervous system activity. Fourier transform, the most commonly used method to analyze variability, does not offer an easy assessment of its dynamics because of limitations inherent in its stationary hypothesis. Conversely, wavelet transform allows analysis of nonstationary signals. We compared the respective yields of Fourier and wavelet transforms in analyzing heart rate variability during dynamic changes in autonomous nervous system balance induced by atropine and propranolol. Fourier and wavelet transforms were applied to sequences of heart rate intervals in six subjects receiving increasing doses of atropine and propranolol. At the lowest doses of atropine administered, heart rate variability increased, followed by a progressive decrease with higher doses. With the first dose of propranolol, there was a significant increase in heart rate variability, which progressively disappeared after the last dose. Wavelet transform gave significantly better quantitative analysis of heart rate variability than did Fourier transform during autonomous nervous system adaptations induced by both agents and provided novel temporally localized information.  (+info)

(8/9497) Excess of high activity monoamine oxidase A gene promoter alleles in female patients with panic disorder.

A genetic contribution to the pathogenesis of panic disorder has been demonstrated by clinical genetic studies. Molecular genetic studies have focused on candidate genes suggested by the molecular mechanisms implied in the action of drugs utilized for therapy or in challenge tests. One class of drugs effective in the treatment of panic disorder is represented by monoamine oxidase A inhibitors. Therefore, the monoamine oxidase A gene on chromosome X is a prime candidate gene. In the present study we investigated a novel repeat polymorphism in the promoter of the monoamine oxidase A gene for association with panic disorder in two independent samples (German sample, n = 80; Italian sample, n = 129). Two alleles (3 and 4 repeats) were most common and constituted >97% of the observed alleles. Functional characterization in a luciferase assay demonstrated that the longer alleles (3a, 4 and 5) were more active than allele 3. Among females of both the German and the Italian samples of panic disorder patients (combined, n = 209) the longer alleles (3a, 4 and 5) were significantly more frequent than among females of the corresponding control samples (combined, n = 190, chi2 = 10.27, df = 1, P = 0.001). Together with the observation that inhibition of monoamine oxidase A is clinically effective in the treatment of panic disorder these findings suggest that increased monoamine oxidase A activity is a risk factor for panic disorder in female patients.  (+info)

numerical data

  • Students develop an understanding of the uses, strengths and limitations of various methods, ethical issues in conducting social inquiry, debates over epistemology, and skills in design, report writing, and interpretation of numerical data. (


  • I am a data scientist and have experience with machine learning and statistical analysis of data using Python and R. I have previously done such projects. (
  • Subject order-independent group ICA (SOI-GICA) for functional MRI data analysis. (
  • Independent component analysis (ICA) is a data-driven approach to study functional magnetic resonance imaging (fMRI) data. (
  • However, due to the usually limited computational capability, data reduction with principal component analysis (PCA: a standard preprocessing step of ICA decomposition) is difficult to achieve for a large dataset. (
  • In the quantitative analysis of behaviour, choice data are most often plotted and analyzed as logarithmic transforms of ratios of responses and of ratios of reinforcers according to the generalized-matching relation, or its derivatives such as conditional-discrimination models. (
  • Covers core topics for students undertaking their own research, including experimental and qualitative methods, sociolinguistics, corpus construction and analysis, data recording, transcription and digital analysis of speech, and speech imaging. (
  • This course concentrates on the collection and analysis of quantitative data and the reporting of results. (
  • In this course students develop a comprehensive understanding of social science methods for the design of social inquiry, the collection and analysis of quantitative data and the reporting of results. (


  • Principles and procedures for statistical interpretation of data. (


  • Simulated and real fMRI experiments were used to demonstrate the subject-order-induced variability of TC-GICA results using multiple PCA data reductions. (


  • Both simulated and real fMRI data experiments demonstrated the high robustness and accuracy of the SOI-GICA results compared to those of traditional TC-GICA. (


  • I have completed a Black Belt project as well as several Green Belt projects applying a number of statistical tools and techniques. (


  • However, linear regression of this type requires that the log choice data be normally distributed, of equal variance for each log reinforcer ratio, and that the x (log reinforcer ratio) measures be fixed with no variance. (


  • Accordingly, we recommend SOI-GICA for group ICA-based fMRI studies, especially those with large data sets. (