220900 Assessing the Causal Effect of Treatment Dosages in the Presence of Self-Selection

Monday, November 8, 2010 : 12:30 PM - 12:41 PM

Xin Gao , Department of Biostatistics, School of Public Health, University of Michigan at Ann Arbor, Ann Arbor, MI
Michael R. Elliott , Department of Biostatistics, School of Public Health, University of Michigan at Ann Arbor, Ann Arbor, MI
To make drug therapy as effective as possible, patients are often put on an escalating dosing schedule. But patients may choose to take a lower dose because of side effects. Thus, even in a randomized trial, the dose level received is a post-randomization variable, and comparison with the control group may no longer have a causal interpretation. Hence we use the potential outcomes framework to define pre-randomization “principal strata” from the joint distribution of doses selected under control and treatment arms, with the goal of estimating the effect of treatment within the subgroups of the population who will select a given set of dose levels. When subjects on the control arm cannot obtain treatment, these principal strata are fully observed on treatment, but remain latent on control. Adverse event information can be used to identify the tolerated dose level in the control arm.

Learning Areas:
Biostatistics, economics

Learning Objectives:
Assess the Causal Effect of Treatment Dosages in the Presence of Self-Selection

Keywords: Clinical Trials, Biostatistics

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am qualified to present because I am graduate student research assistant working on this project.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.