An Introduction of Missing Data Handling in Clinical Trials

Missing data with ignorable missingness or non-ignorable missingness often occur in clinical trials, which can arise from various sources. In this talk, we will first discuss various scenarios of missing data occurrence in clinical trials and elucidate the rationale behind the selection of handling method along with illustrative case examples, and then delve into a detailed discussion of Pattern mixture models (PMMs), which provide a flexible approach by considering different patterns of missingness and are commonly used to assess treatment effects for clinical trials with non-ignorable missing data.

missing data

multiple imputation

pattern mixture models