Accounting for baseline differences and measurement error in the analysis of change over time

Authors

  • Julia Braun,

    Corresponding author
    1. Division of Biostatistics, Institute for Social and Preventive Medicine, University of Zurich, 8001 Zurich, Switzerland
    • Correspondence to: Julia Braun, Division of Biostatistics, Institute for Social and Preventive Medicine, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland.

      E-mail: julia.braun@ifspm.uzh.ch

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  • Leonhard Held,

    1. Division of Biostatistics, Institute for Social and Preventive Medicine, University of Zurich, 8001 Zurich, Switzerland
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  • Bruno Ledergerber,

    1. Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, 8091 Zurich, Switzerland
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  • the Swiss HIV Cohort Study

    1. Division of Biostatistics, Institute for Social and Preventive Medicine, University of Zurich, 8001 Zurich, Switzerland
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  • The members of the Swiss HIV Cohort Study are as follows: Aubert V, Barth J, Battegay M, Bernasconi E, Böni J, Bucher HC, Burton-Jeangros C, Calmy A, Cavassini M, Egger M, Elzi L, Fehr J, Fellay J, Francioli P, Furrer H (Chairman of the Clinical and Laboratory Committee), Fux CA, Gorgievski M, Günthard H (President of the SHCS), Haerry D (deputy of ‘Positive Council’), Hasse B, Hirsch HH, Hirschel B, Hösli I, Kahlert C, Kaiser L, Keiser O, Kind C, Klimkait T, Kovari H, Ledergerber B, Martinetti G, Martinez de Tejada B, Metzner K, Müller N, Nadal D, Pantaleo G, Rauch A (Chairman of the Scientific Board), Regenass S, Rickenbach M (Head of Data Center), Rudin C (Chairman of the Mother & Child Substudy), Schmid P, Schultze D, Schöni-Affolter F, Schüpbach J, Speck R, Taffé P, Tarr P, Telenti A, Trkola A, Vernazza P, Weber R and Yerly S.

Abstract

If change over time is compared in several groups, it is important to take into account baseline values so that the comparison is carried out under the same preconditions. As the observed baseline measurements are distorted by measurement error, it may not be sufficient to include them as covariate. By fitting a longitudinal mixed-effects model to all data including the baseline observations and subsequently calculating the expected change conditional on the underlying baseline value, a solution to this problem has been provided recently so that groups with the same baseline characteristics can be compared. In this article, we present an extended approach where a broader set of models can be used. Specifically, it is possible to include any desired set of interactions between the time variable and the other covariates, and also, time-dependent covariates can be included. Additionally, we extend the method to adjust for baseline measurement error of other time-varying covariates. We apply the methodology to data from the Swiss HIV Cohort Study to address the question if a joint infection with HIV-1 and hepatitis C virus leads to a slower increase of CD4 lymphocyte counts over time after the start of antiretroviral therapy. Copyright © 2013 John Wiley & Sons, Ltd.

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