Literature DB >> 3667863

Interpreting time-related trends in effect estimates.

S Greenland1.   

Abstract

This paper reviews the sources of apparent time trends in effect. Apparent changes in effect may arise from changes in covariate distributions, background rates, exposure distribution, measurement quality, or selection factors. As with time trends in rates, time trends in effect must have at least one of these sources, since time itself has no effect. If background incidence is changing, however, time trends in effect become dependent on choice of effect measure, and interpretation must take this into account. Evidence that a trend arises from age-, cohort-, or period-related phenomena can indicate the relative plausibility of different explanations of the trend. Conversely, the relative plausibility of each explanation may indicate whether the trend is most appropriately viewed over the axis of age, birth cohort, or calendar time. Nevertheless, studies of short duration relative to an apparent trend (such as most case-control studies) must invoke strong assumptions to justify focusing on a particular axis. Illustrations are given from studies of electronic fetal monitoring and of smoking and lung cancer.

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Year:  1987        PMID: 3667863     DOI: 10.1016/s0021-9681(87)80005-x

Source DB:  PubMed          Journal:  J Chronic Dis        ISSN: 0021-9681


  9 in total

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2.  Misclassification of seat belt use.

Authors:  P Cummings; F P Rivara
Journal:  Inj Prev       Date:  2003-03       Impact factor: 2.399

3.  Bias in estimates of seat belt effectiveness.

Authors:  T D Koepsell; F P Rivara; D C Grossman; C Mock
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4.  Guillain-Barre syndrome following quadrivalent human papillomavirus vaccination among vaccine-eligible individuals in the United States.

Authors:  Rohit P Ojha; Bradford E Jackson; Joseph E Tota; Tabatha N Offutt-Powell; Karan P Singh; Sejong Bae
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5.  Association of rear seat safety belt use with death in a traffic crash: a matched cohort study.

Authors:  Motao Zhu; Peter Cummings; Haitao Chu; Lawrence J Cook
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6.  Confounding due to changing background risk in adaptively randomized trials.

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Journal:  Clin Trials       Date:  2011-05-24       Impact factor: 2.486

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Authors:  Shan H Siddiqi; Nicholas T Trapp; Carl D Hacker; Timothy O Laumann; Sridhar Kandala; Xin Hong; Ludwig Trillo; Pashtun Shahim; Eric C Leuthardt; Alexandre R Carter; David L Brody
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Review 8.  Basic problems in interaction assessment.

Authors:  S Greenland
Journal:  Environ Health Perspect       Date:  1993-12       Impact factor: 9.031

9.  Including non-concurrent control patients in the analysis of platform trials: is it worth it?

Authors:  Kim May Lee; James Wason
Journal:  BMC Med Res Methodol       Date:  2020-06-24       Impact factor: 4.615

  9 in total

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