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    ABSTRACT: This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal effects of interest in a conditional mean model for a continuous response given time-varying treatments and moderators. We present an easy-to-use estimator of the SNMM that combines an existing regression-with-residuals (RR) approach with an inverse-probability-of-treatment weighting (IPTW) strategy. The RR approach has been shown to identify the moderated time-varying causal effects if the time-varying moderators are also the sole time-varying confounders. The proposed IPTW+RR approach provides estimators of the moderated time-varying causal effects in the SNMM in the presence of an additional, auxiliary set of known and measured time-varying confounders. We use a small simulation experiment to compare IPTW+RR versus the traditional regression approach and to compare small and large sample properties of asymptotic versus bootstrap estimators of the standard errors for the IPTW+RR approach. This article clarifies the distinction between time-varying moderators and time-varying confounders. We illustrate the methodology in a case study to assess if time-varying substance use moderates treatment effects on future substance use. Copyright © 2013 John Wiley & Sons, Ltd.
    No preview · Article · Sep 2014 · Statistics in Medicine
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    ABSTRACT: Nearly 23% of all telephone interviews in the most recently completed wave of the Panel Study of Income Dynamics break off at least once, requiring multiple sessions to complete the interview. Given this high rate, a study was undertaken to better understand the causes and consequences of temporary breakoffs in a computer-assisted telephone interview setting. The majority of studies examining breakoffs have been conducted in the context of self-administered web surveys. The present study uses new paradata collected on telephone interview breakoffs to describe their prevalence, associated field effort, the instrument sections and questions on which they occur, their source - whether respondent-initiated, interviewer-initiated, or related to telephone problems - and associations with respondent and interviewer characteristics. The results provide information about the survey response process and suggest a set of recommendations for instrument design and interviewer training, as well as additional paradata that should be collected to provide more insight into the breakoff phenomenon.
    No preview · Article · Dec 2013 · Survey Research Methods

  • No preview · Article · Dec 2013 · Nicotine & Tobacco Research
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