Applying concepts of generalizability theory on clinical trial data to investigate sources of variation and their impact on reliability

Abstract

This work aims at applying concepts of generalizability theory to data resulting from clinical trials. The focus is to study the sources of variance and their impact on the reliability and generalizability of a psychiatric measurement scale. The goal is to identify, measure, and thereby potentially find strategies to reduce the influence of these sources on the measurement in question for future trials. This approach was originally devised by Cronbach and his associates and is known as generalizability theory. This work shows how full modeling power in mixed models can be used to study generalizability using data from five double-blind randomized clinical trials, comparing the effects of risperidone to conventional antipsychotic agents for the treatment of chronic schizophrenia.