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<span style="font-size: 12pt; font-family: Calibri, Helvetica, sans-serif;">Dear all,</span></div>
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<span style="font-size: 12pt; font-family: Calibri, Helvetica, sans-serif;">Hope everyone is having a good week.</span></div>
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<span style="font-size: 12pt; font-family: Calibri, Helvetica, sans-serif;">Just a reminder that, a</span><span style="font-size: 12pt; font-family: Calibri, Helvetica, sans-serif;">t today's S3RI seminar</span><span style="font-size: 12pt; font-family: Calibri, Helvetica, sans-serif;"> </span><span style="font-size: 12pt; background-color: white; font-family: Calibri, Helvetica, sans-serif;">at
2 pm</span><span style="font-size: 12pt; font-family: Calibri, Helvetica, sans-serif;">, Prof Geert Verbeke (KU Leuven, Hasselt University) is speaking to us about</span>
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<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; color: black; font-family: Calibri, Helvetica, sans-serif;">"How to correct for baseline covariates in longitudinal clinical trials?"</span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
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<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; color: black; background-color: white; font-family: Calibri, Helvetica, sans-serif;">Please see below for the details of the talk and how to
join the seminar online.</span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
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<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; color: black; background-color: white; font-family: Calibri, Helvetica, sans-serif;">Hope to see you at the seminar today (at 2 pm)!</span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
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</span><span style="margin: 0px; font-size: 12pt; color: black; background-color: white; font-family: Calibri, Helvetica, sans-serif;">Jessie</span></p>
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<span style="margin: 0px; font-size: 15px; font-family: Calibri, Arial, Helvetica, sans-serif; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255);"><span style="margin:0px; font-size:12pt; font-family:Calibri,Helvetica,sans-serif"><b><em><strong>How
to correct for baseline covariates in longitudinal clinical trials?</strong></em></b></span></span></span></p>
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<span style="margin:0px; font-size:12pt"><i></i></span><span style="font-family:Calibri,Helvetica,sans-serif; font-size:12pt">Geert Verbeke (KU Leuven, Hasselt University)</span><i><span style="margin: 0px; font-size: 12pt; background-color: rgb(255, 255, 255); display: inline !important;"></span></i></div>
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<span style="margin: 0px; font-size: 12pt; font-family: Calibri, Arial, Helvetica, sans-serif; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255);"></span><span style="font-family:Calibri,Helvetica,sans-serif; font-size:12pt">In clinical trials, mixed
models are becoming more popular for the analysis of longitudinal data. The main motivation is often expected dropout which can easily be handled through the analysis of the longitudinal trajectories. In many situations, analyses are corrected for baseline
covariates such as study site or stratification variables. Key questions are then how to perform a longitudinal analysis correcting for baseline covariates, and how sensitive are the results with respect to choices made and models used?</span>
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<span style="font-family:Calibri,Helvetica,sans-serif; font-size:12pt">In this presentation, we will first present and compare a number of techniques available to correct for baseline covariates within the context of the linear mixed model for continuous outcomes.
Second, we will study the sensitivity of the various techniques in case the baseline correction is based on a wrong model or does not include important covariates. Finally, our findings will be used to formulate some general guidelines relevant in a clinical
trial context. All findings and results will be illustrated extensively using data from a real clinical trial.</span>
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