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Tips for Researchers on Completing the Data Analysis Section of the IRB Application

Tips for Researchers on Completing the Data Analysis Section of the IRB Application . Don Allensworth-Davies, MSc Statistical Manager, Data Coordinating Center Boston University School of Public Health IRB Reviewer, Panel Blue February 15, 2006.

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Tips for Researchers on Completing the Data Analysis Section of the IRB Application

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  1. Tips for Researchers on Completing the Data Analysis Section of the IRB Application Don Allensworth-Davies, MSc Statistical Manager, Data Coordinating Center Boston University School of Public Health IRB Reviewer, Panel Blue February 15, 2006

  2. “To write it, it took three months; to conceive it three minutes; to collect the data in it — all my life.” F. Scott Fitzgerald, referring to his novel This Side of Paradise in a letter to the Booksellers’ Convention, April 1920

  3. Data Analysis and Human Subjects Protection Research means a systematic investigation, including research development, testing and evaluation, designed to develop or contribute to generalizable knowledge. §46.102(d) Definitions, Federal Regulations Title 45, Public Welfare, Department of Health and Human Services, Part 46, Protection of Human Subjects

  4. Data Analysis and Human Subjects Protection (cont’d) Risks to subjects are minimized: (i) By using procedures which are consistent with sound research design and which do not unnecessarily expose subjects to risk, and (ii) whenever appropriate, by using procedures already being performed on the subjects for diagnostic or treatment purposes. §46.111 Criteria for IRB Approval of Research, Federal Regulations Title 45, Public Welfare, Department of Health and Human Services, Part 46, Protection of Human Subjects

  5. IRB: Ethics and Human Research, September-October 2003 Available on the IRB Website

  6. What the IRB Considers in Reviewing an Analysis • Is the sample size adequate to answer the research question? • Is the sample size large enough to ensure sufficient data to answer the research question? • Is the sample size justified?

  7. What the IRB Considers in Reviewing an Analysis (cont’d) • Is the analysis plan clearly described and adequate to answer the research question? • Is it clear which variables will be analyzed? • Is it clear what comparisons will be made? • Are the methods being used appropriate for the study design and the information that was collected? • How will the researcher know whether or not the study objectives have been met?

  8. Where Data Analysis Appears on the IRB Application

  9. Tip #1: Remember to Include All ‘At Risk’ Subjects and Withdrawals in Total Sample Size Sample Size= Consent and fully participate in study + Expected dropouts, withdrawals, and terminations + For some studies: Screened and not enrolled -IF- subjects were placed ‘at risk’ during screening (e.g., blood draws, collection of identifiable information)

  10. Sample Size and the IRB Application

  11. Sample Size and the IRB Application: Special Considerations • International Research • If a BUMC researcher will be conducting research and having contact with human subjects in another country, then these subjects may "belong to BUMC" and therefore should be reported in both the local and worldwide sample sizes

  12. Sample Size and the IRB Application: Special Considerations (cont’d) • Research Involving Proxy Data Collection • If data are being collected about both the subject and, through them, about another person then both should be counted in the sample size • Examples: Mother-child studies, studies of primary relationship or sexual partners, twins’ studies • If a study involves interviewing multiple groups (e.g., surveying patient, MDs, nurses, and social workers) ALL SUBJECTS should be considered in the sample size

  13. Sample Size and the IRB Progress Report Should not exceed total approved by IRB

  14. Sample Size and the IRB Progress Report

  15. Tip #2: Correctly Justify the Sample Size • Option #1: Traditional power calculation describing power that will be achieved to detect a specific difference or change • Option #2: Feasibility • Based on the researcher’s knowledge of the potential subject pool • Based on the resources available to the researcher to conduct the study

  16. Tip #2: Correctly Justify the Sample Size (cont’d) IMPORTANT: Simply stating that the research is a pilot study is NOT adequate justification of sample size

  17. Tip #3: Clearly Describe Each Analysis That Will Be Performed Example: “Study Objective #1, Identify Demographic Differences in Unsafe Sexual Behavior: To test for differences in proportions between different groups classified by sex, age, country of birth, education, and income, we will use chi-square or Fisher's exact tests (if data are sparse). We will present test statistics and associated p-values. Conventional criteria (p < 0.05) will be used to identify statistically significant differences. Significant differences between the study groups may indicate potential confounding, and we will adjust using logistic regression models for these potential confounders, if they are found ultimately to be associated with our study outcome of unsafe sexual behavior.”

  18. Tip #3: Clearly Describe Each Analysis That Will Be Performed (cont’d) • Variables to be analyzed: sex, age, country of birth, education, income, unsafe sexual behavior • Comparisons to be made: test for differences in proportions • Methods to be used: chi-square or Fisher's exact tests (if data are sparse) • Appropriate for categorical bivariate analyses? Yes

  19. Tip #3: Clearly Describe Each Analysis That Will Be Performed (cont’d) • How will the researcher know if the study objective has been met (i.e., if there is a difference in proportions)? Conventional criteria (p < 0.05) will be used to assess statistically significant differences • In this example researcher went one step further and also proposed analytic methods to help control for bias/confounding

  20. Tip #4: Remember That Some Study Designs Require Special Methods • Randomized clinical trials • Once randomized, always analyzed • Longitudinal and case-crossover studies • Methods for repeated measures or pairs • Matched case-control studies • Methods that take the matching into account • Focus groups and open-ended subject interviews • Qualitative methods

  21. Characteristics of a Good Analysis Plan • Parsimonious • Only includes the variables needed to answer the research question • Avoids (or adjusts for) multiple comparisons • Clearly Described • Comparison(s) to evaluate each study objective • Methods that will be used • How the researcher will know if the objective has been reached and their hypothesis proved/disproved

  22. Analytic Resources for BUMC Researchers Data Coordinating Center, BUSPH http://www.bu.edu/dbin/sph/research_centers/dcc.php Department of Biostatistics, BUSPH http://www.bu.edu/dbin/sph/departments/biostatistics

  23. General Clinical Research Center Investigators If you are currently a GCRC researcher –OR– If you are preparing an application to use the GCRC The GCRC can provide assistance with development of the study design and analysis plan http://dccwww.bumc.bu.edu/gcrcweb/abouttheGCRC.htm

  24. Questions and Discussion

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