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Enhancement of SAS and R for meta-analysis of observational studies

Nicolet, Deedra Rae
http://rave.ohiolink.edu/etdc/view?acc_num=osu1407409901

Abstract Details

2006, Master of Science, Ohio State University, Public Health.
Meta-analysis is used to get an overall effect estimate from a collection of previously conducted studies on the same subject. When this method first became popular, it was in the setting of clinical trials. Meta-analysis identifies homogeneity of effect estimates between studies. This type of analysis also takes into consideration confounding factors and decreases their effect on the estimate. Meta-analysis consists of searching the literature for relevant studies, deciding which studies to include in the analysis, extracting relevant information and analyzing the data. The goal of meta-analysis is to estimate the effect estimate from a collection of relevant studies. In order to find this estimate, we consider two possible models for the data. The data could be fit using a fixed-effects or random-effects model. The fixed-effects model has two popular methods of finding the estimate that we will consider here, the Mantel-Haenszel method and the confidence interval method. This model is based on the assumption that there is only a within study variance component. The random-effects model is the second model that we address and in this case, we examine the DerSimonian-Laird method for estimating the effect estimate. There is an additional variance component that is used in the random-effects model. This variance component addresses the variance between studies. Meta-analysis has been extensively used with clinical trials and observational studies. In available statistical software, the programs available for meta-analysis can only be used with clinical trials. The goal of this work was to modify the programs in R and SAS, so they would be suitable for use with observational studies. Using data on aspirin use and its effect on colon cancer, we demonstrate the use of the modified R and SAS code. The results presented here demonstrated how we extended the programs for meta¬-analysis of clinical trials to observational studies. As these are very common in medical studies, this development will allow additional analysis to be done when they are the object of a given study. The hope for this work is to provide researchers with programs suitable for meta-analysis with observational studies and clinical trials.
Randall Harris (Advisor)
Deborah Burr Doss (Advisor)
69 p.
Public Health

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Citations

  • Nicolet, D. R. (2006). Enhancement of SAS and R for meta-analysis of observational studies [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1407409901

    APA Style (7th edition)

  • Nicolet, Deedra. Enhancement of SAS and R for meta-analysis of observational studies. 2006. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1407409901.

    MLA Style (8th edition)

  • Nicolet, Deedra. "Enhancement of SAS and R for meta-analysis of observational studies." Master's thesis, Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=osu1407409901

    Chicago Manual of Style (17th edition)

osu1407409901
208
© 2006, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.