RTI Press Method Report

A mixed model approach for intent-to-treat analysis in longitudinal clinical trials with missing values

Chakraborty, H., & Gu, H. (March 2009).

Full Document: RTI Press - Methods Report PDF

Permanent Link: doi:10.3768/rtipress.2009.mr.0009.0903

Full Citation: Chakraborty, H., & Gu, H. (March 2009). A mixed model approach for intent-to-treat analysis in longitudinal clinical trials with missing values. RTI Press Publication No. MR-0009-0903.

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Abstract

Missing values and dropouts are common issues in longitudinal studies in all
areas of medicine and public health. Intent-to-treat (ITT) analysis has become a widely accepted method for the analysis of controlled clinical trials. In most controlled clinical trials, some patients do not complete their intended followup according to the protocol for a variety of reasons; this problem generates missing values. Missing values lead to concern and confusion in identifying the ITT population, which makes the data analysis more complex and challenging. No adequate strategy exists for ITT analyses of longitudinal controlled clinical trial data with missing values. Several ad hoc strategies for dealing with missing values for an ITT analysis are common in the practice of controlled clinical trials.
We performed a detailed investigation based on simulation studies to develop
recommendations for this situation. We compared sizes (type I errors) and
power between some popular ad hoc approaches and the linear mixed model
approach under different missing value scenarios. Our results suggest that, for
studies with a high percentage of missing values, the mixed model approach
without any ad hoc imputation is more powerful than other options.

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