CISMAC Webinar June 3: Multivariable regression – adjusting for covariates in an RCT
Bireshwar Sinha will speak about: Multivariable regression to analyze data from a Randomized controlled trial (RCT) of community-initiated Kangaroo Mother Care and postartum depression: Why and when to adjust for covariates in an RCT? Abstract: A good analytic epidemiologic study should ensure that the estimated association, such as the effect of an intervention, is not affected by selection/confounding bias or by information bias. The purpose of multivariable models is to control for potential confounding bias, thereby enhancing the likelihood that the measure of association is a true representation of a causal effect. In a perfectly conducted large randomized controlled trial Continue reading CISMAC Webinar June 3: Multivariable regression – adjusting for covariates in an RCT