Biostatistics for Better Health Solutions: How to Jointly Analyze Longitudinal Data and Time-To-Dropout Or Time-To-Death Simultaneously: An Integrative Data Harmonization Approach

Drawing on theory and prior research, evidence-based research can generate data from different sources and phases of research. A central feature of evidence-based research is the sequential and longitudinal implementation of data analysis allowing research participants to be removed for various study related end-points throughout the research timeline. This how-to seminar is to primarily give an overview of pitfalls in longitudinal data analysis and further discuss an integrative data harmonization with joint modeling of longitudinal data and time-to-event (such as dropout and censored) data simultaneously using real data from a HIV/AIDS clinical trial. We demonstrate that an integrative data harmonization has the potential to produce a more efficient and more powerful statistical analysis.

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