• Power and sample size for multistate model analysis of longitudinal discrete outcomes in disease prevention trials

    Type Journal Article
    Author Isabelle L. Smith
    Author Jane E. Nixon
    Author Linda Sharples
    URL http://onlinelibrary.wiley.com/doi/abs/10.1002/sim.8882
    Rights © 2021 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.
    Volume n/a
    Issue n/a
    Publication Statistics in Medicine
    ISSN 1097-0258
    Date 2021
    Extra _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.8882
    DOI https://doi.org/10.1002/sim.8882
    Accessed 2/12/2021, 11:20:57 AM
    Library Catalog Wiley Online Library
    Language en
    Abstract For clinical trials where participants pass through a number of discrete health states resulting in longitudinal measures over time, there are several potential primary estimands for the treatment effect. Incidence or time to a particular health state are commonly used outcomes but the choice of health state may not be obvious and these estimands do not make full use of the longitudinal assessments. Multistate models have been developed for some diseases and conditions with the purpose of understanding their natural history and have been used for secondary analysis to understand mechanisms of action of treatments. There is little published on the use of multistate models as the primary analysis method and potential implications on design features, such as assessment schedules. We illustrate methods via analysis of data from a motivating example; a Phase III clinical trial of pressure ulcer prevention strategies. We clarify some of the possible estimands that might be considered and we show, via a simulation study, that under some circumstances the sample size could be reduced by half using a multistate model based analysis, without adversely affecting the power of the trial.
    Date Added 2/12/2021, 11:20:57 AM
    Modified 2/25/2021, 8:34:44 AM

    Tags:

    • key
    • longitudinal
    • markov
    • multi-state-model
    • multiple-endpoints
    • multiple-states
    • ordinal
    • power
    • rct
    • sample-size
    • serial
    • teaching-mds
    • transition-model

  • Repeated measures in clinical trials: Simple strategies for analysis using summary measures

    Type Journal Article
    Author Stephen Senn
    Author Lynda Stevens
    Author Nish Chaturvedi
    URL https://pubmed.ncbi.nlm.nih.gov/10734289
    Volume 19
    Pages 861-877
    Publication Stat Med
    Date 2000
    Extra Citation Key: sen00rep tex.citeulike-article-id= 13265118 tex.citeulike-linkout-0= http://dx.doi.org/10.1002/(SICI)1097-0258(20000330)19:6%3C861::AID-SIM407%3E3.0.CO;2-F tex.posted-at= 2014-07-14 14:09:49 tex.priority= 0
    DOI 10.1002/(SICI)1097-0258(20000330)19:6<861::AID-SIM407>3.0.CO;2-F
    Date Added 7/7/2018, 1:38:33 PM
    Modified 6/12/2020, 6:11:53 AM

    Tags:

    • serial-data
    • teaching-mds
    • repeated-measures
    • summary-measures
    • auc
    • slope

  • Regression models for the analysis of pretest/posttest data

    Type Journal Article
    Author Julio M. Singer
    Author Dalton F. Andrade
    URL http://dx.doi.org/10.2307/2533973
    Volume 53
    Pages 729-735
    Publication Biometrics
    Date 1997
    Extra Citation Key: sin97reg tex.citeulike-article-id= 13264865 tex.citeulike-linkout-0= http://dx.doi.org/10.2307/2533973 tex.posted-at= 2014-07-14 14:09:44 tex.priority= 0
    DOI 10.2307/2533973
    Date Added 7/7/2018, 1:38:33 PM
    Modified 11/8/2019, 8:01:59 AM

    Tags:

    • serial-data
    • teaching-mds
    • repeated-measures
    • change
    • analysis-of-change
    • baseline-measurement-as-covariable
    • multiplicative-model
    • pretest-posttest

    Notes:

    • problems with using baseline measurement as covariate

  • A refinement to the analysis of serial data using summary measures

    Type Journal Article
    Author J. N. S. Matthews
    URL http://dx.doi.org/10.1002/sim.4780120105
    Volume 12
    Pages 27-37
    Publication Stat Med
    Date 1993
    Extra Citation Key: mat93ref tex.citeulike-article-id= 13264584 tex.citeulike-linkout-0= http://dx.doi.org/10.1002/sim.4780120105 tex.posted-at= 2014-07-14 14:09:38 tex.priority= 0
    DOI 10.1002/sim.4780120105
    Date Added 7/7/2018, 1:38:33 PM
    Modified 11/8/2019, 8:01:59 AM

    Tags:

    • longitudinal-data
    • serial-data
    • teaching-mds
    • weighting
    • summary-measures
    • auc
    • area-under-the-curve
    • weighting-each-subject-differently

  • Analysis of serial measurements in medical research

    Type Journal Article
    Author J. N. S. Matthews
    Author Douglas G. Altman
    Author M. J. Campbell
    Author Patrick Royston
    URL http://dx.doi.org/10.1136/bmj.300.6719.230
    Volume 300
    Pages 230-235
    Publication BMJ
    Date 1990
    Extra Citation Key: mat90ana tex.citeulike-article-id= 13264583 tex.citeulike-linkout-0= http://dx.doi.org/10.1136/bmj.300.6719.230 tex.posted-at= 2014-07-14 14:09:38 tex.priority= 0 Letter to editor by S. Senn in same issue
    DOI 10.1136/bmj.300.6719.230
    Date Added 7/7/2018, 1:38:33 PM
    Modified 11/8/2019, 8:01:59 AM

    Tags:

    • serial-data
    • teaching-mds
    • summary-measures
    • repeated-measurements
    • growth-curve
    • peak-vs-growth-relationships
    • relating-peak-to-time-to-peak