Analysis of Pre-test-Post-test Data
A pretest-posttest research design is a simple form of a repeated-measures design where a baseline measurement is taken on subjects randomized to control and intervention groups followed by a post-intervention measurement on the same groups. Generally, the analysis is based on testing three hypotheses concerning (1) the difference in pretest measurements between the control and the intervention groups, (2) change (gain) in response for individual groups, and (3) the difference in gain between groups. There are several statistical methods that are suitable for a pretest-posttest design analysis. This workshop will highlight important differences in the analysis approaches in order to facilitate selecting an appropriate analysis method.
Fee: None to members of the Cornell community, but registration is required.
For times and locations of upcoming workshops, please see the Workshop Schedule.