Assessing the quality of reports of randomized clinical trials : is blinding necessary?

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Using Multivariate Statistics

Examines whether the positive association between social support and well-being is attributable more to an overall beneficial effect of support (main- or direct-effect model) or to a process of support protecting persons from potentially adverse effects of stressful events (buffering model). The review of studies is organized according to (1) whether a measure assesses support structure (the existence of relationships) or function (the extent to which one's interpersonal relationships provide particular resources) and (2) the degree of specificity (vs globality) of the scale. Special attention is given to methodological characteristics that are requisite for a fair comparison of the models. It is concluded that there is evidence consistent with both models. Evidence for the buffering model is found when the social support measure assesses the perceived availability of interpersonal resources that are responsive to the needs elicited by stressful events. Evidence for a main effect model is found when the support measure assesses a person's degree of integration in a large social network. Both conceptualizations of social support are correct in some respects, but each represents a different process through which social support may affect well-being. Implications for theories of social support processes and for the design of preventive interventions are discussed.

/pdf/stress-social-support-and-the-buffering-hypothesis-37b7abjbst.pdf

Stress, social support, and the buffering hypothesis.

https://surfer.nmr.mgh.harvard.edu/ftp/articles/desikan06-parcellation.pdf

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

Protocols of systematic reviews and meta-analyses allow for planning and documentation of review methods, act as a guard against arbitrary decision making during review conduct, enable readers to assess for the presence of selective reporting against completed reviews, and, when made publicly available, reduce duplication of efforts and potentially prompt collaboration. Evidence documenting the existence of selective reporting and excessive duplication of reviews on the same or similar topics is accumulating and many calls have been made in support of the documentation and public availability of review protocols. Several efforts have emerged in recent years to rectify these problems, including development of an international register for prospective reviews (PROSPERO) and launch of the first open access journal dedicated to the exclusive publication of systematic review products, including protocols (BioMed Central's Systematic Reviews). Furthering these efforts and building on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines, an international group of experts has created a guideline to improve the transparency, accuracy, completeness, and frequency of documented systematic review and meta-analysis protocols--PRISMA-P (for protocols) 2015. The PRISMA-P checklist contains 17 items considered to be essential and minimum components of a systematic review or meta-analysis protocol.This PRISMA-P 2015 Explanation and Elaboration paper provides readers with a full understanding of and evidence about the necessity of each item as well as a model example from an existing published protocol. This paper should be read together with the PRISMA-P 2015 statement. Systematic review authors and assessors are strongly encouraged to make use of PRISMA-P when drafting and appraising review protocols.

/pdf/preferred-reporting-items-for-systematic-review-and-meta-mgb1uy0yle.pdf

Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation.

1. Introduction 2. Basic concepts 3. Devising the items 4. Scaling responses 5. Selecting the items 6. Biases in responding 7. From items to scales 8. Reliability 9. Generalizability theory 10. Validity 11. Measuring change 12. Item response theory 13. Methods of administration 14. Ethical considerations 15. Reporting test results Appendices

Health Measurement Scales: A Practical Guide to Their Development and Use

Cronbach's a is the most widely used index of the reliability of a scale. However, its use and interpretation can be subject to a number of errors. This article discusses the historical development of a from other indexes of internal consistency (split-half reliability and Kuder-Richardson 20) and discusses four myths associated with a: (a) that it is a fixed property of the scale, (b) that it measures only the internal consistency of the scale, (c) that higher values are always preferred over lower ones, and (d) that it is restricted to the range of 0 to 1. It provides some recommendations for acceptable values of a in different situations.

Starting at the beginning: An introduction to coefficient alpha and internal consistency

Health Measurement Scales

Section 1: THE NATURE OF DATA AND STATISTICS 1. The Basics 2. Looking at the Data: A First Look at Graphing Data 3. Describing the Data with Numbers: Measures of Central Tendency and Dispersion 4. The Normal Distribution 5. Probability 6. Elements of Statistical Inference C.R.A.P. Detectors Section 2: ANALYSIS OF VARIANCE 7. Comparing Two Groups: The t-Test 8. More than Two Groups: One-Way ANOVA 9. Factorial ANOVA 10. Two Repeated Observations: The Paired t-Test and Alternatives 11. Repeated Measures ANOVA 12. Multivariate ANOVA (MANOVA) C.R.A.P. Detectors Section 3: REGRESSION AND CORRELATION 13. Simple Regression and Correlation 14. Multiple Regression 15. Logistic Regression 16. Advanced Topics in Regression and ANOVA 17. Measuring Change 18. Principal Components and Factor Analysis: Fooling Around with Factors 19. Structural Equation Modeling C.R.A.P. Detectors Section 4: NONPARAMETRIC STATISTICS 20. Tests of Significance for Categorical Frequency Data 21. Measures of Association for Categorical Data 22. Tests of Significance for Ranked Data 23. Measures of Association for Ranked Data 24. Life Table (Survival) Analysis C.R.A.P. Detectors Section 5: REPRISE 25. Screwups, Oddballs, and other Vagaries of Science: Locating Outliers, Handling Missing Data, and Transformations 26. Putting It All Together Test Yourself (Being a Compendium of Questions and Answers) Answers to Chapter Exercises References and Further Readings Unabashed Glossary Appendices

Biostatistics : The Bare Essentials

https://www.acilci.net/wp-content/uploads/2014/02/Guidelines-for-reporting-reliability-and-agreement-studies-GRRAS-were-proposed.pdf

David L. Streiner

Papers

Health Measurement Scales: A Practical Guide to Their Development and Use

Starting at the beginning: An introduction to coefficient alpha and internal consistency

Health Measurement Scales

Biostatistics : The Bare Essentials

Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were proposed.