Powerpoint slides from presentation by James Bell ‘Implementing Estimands in Trials: Detailed Clinical Objectives’, 3rd June 2019, PSI conference.
Category Archives: DIA working group
DIA working group
Multiple Imputation requires the modelling of incomplete data under formal assumptions about the combined model for observed and unobserved data (the imputation model). Generalized Linear Mixed Models provide a natural framework for modelling repeated observations, especially for non-Gaussian outcomes. The … Continue reading
Multiple imputation for time to event data under Kaplan-Meier, Cox or piecewise-exponential frameworks – SAS macros
Multiple imputation (MI) and analysis of imputed time-to-event data is implemented in a collection of SAS macros based on the methodology described in the following publications:  Lipkovich I, Ratitch B, O’Kelly M (2016) Sensitivity to censored-at-random assumption in the … Continue reading
Latest update 13 February 2019 Quick summary In the past, many trials have stopped collection of data following discontinuation of randomised treatment. However, more recently data collection continues after randomised treatment discontinuation, since the occurrence of this event is irrelevant … Continue reading