At the end of the course, the student will be able to develop a complex analysis plan to answer a clinical research question, to carry out the analyses using the statistical package SAS, to verify the appropriateness of the analyses based on the findings, and to report and interpret the results.
In particular, the student will be able to: i) understand the purpose of regression analysis, and be able to differentiate between various forms of regression including linear, logistic, poisson, and Cox-proportional hazards regression; ii) understand the requirements for each regression method and be able to adjust the methods to account for or examine: clustering within data structure/sampling frame; hierarchical structures within data; repeated-measures and longitudinal data; iii) be able to evaluate the validity of the results from each type of regression based on statistical criteria; iv) understand different methods for variable selection in regression models; v) be able to interpret and present the results from each type of regression model in a manner that is meaningful to clinicians and applied health scientists.
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