Advanced Statistics for Clinical Science Assignment
In this assignment, you will explore and apply the science of meta analysis. Using the example below and the materials provided in Blackboard, complete each of the following questions.
A nephrologist from Hahnemann University Hospital contacts you about a discrepancy she notices in the literature about the benefits of aerobic exercise on low-density lipoprotein cholesterol (LDL-C) in renal disease patients. You determine that meta-analysis is the appropriate statistical procedure to address this discrepancy. Using the PowerPoint presentation from class, and the Excel calculator, PDFs, and STATA output files, please answer the following questions.
1. What is the research question that we intend to address with meta-analysis?
2. How would you define the criteria for your inclusion/exclusion checklist (i.e. what characteristics must the studies possess to be considered further)?
3. When running your systematic search, whom should you consult? Describe how you should conduct your search procedure to yield as many relevant studies as possible, and how others will be able to replicate your search.
4. You retrieve 500 studies from your systematic search. What should you do to narrow the list of studies down before conducting your coding procedure?
5. After completing the procedure for question 4, you narrow your search down to three studies. How many coders will you use and why? How will you verify if the coding procedure was completed accurately and reliably?
6. Once your coding procedure is completed, you need to determine your effect sizes. Using the Effect Size Excel calculator from class, review the three studies retrieved from the systematic search and compute the appropriate effect size values with Becker's d+.
7. Using the STATA output file, interpret the mean effect size value forthethree studies. What is the mean raw effect size value? Does it have clinical significance?
8. Using the STATA output file, interpret the meta-regressionstatisticsfor thethree studies. What is the R-squared value? Are any of the baseline predictors (age, body mass index [BMI], LDL-C) significant? If so, which predictors?
9. Using the STATA output file, interpret the Q statistic. What does the Q statistic tell us?
10. Based upon your findings from the meta-analytic procedures, what can be concluded about exercise studies to date regarding its impact on LDL-C in renal disease patients? What would you advise and recommend for researchers to consider when conducting future research studies?
Attachment:- Assignment Files.rar