Literature DB >> 14695636

Meta-analysis for trend estimation.

Jian Qing Shi1, J B Copas.   

Abstract

Grouped dose measures, heterogeneity and publication bias are three major problems for meta-analysis in trend estimation. In this paper, we propose a model that allows for arbitrarily aggregated dose levels, and show that the resulting estimates and standard errors can be quite different from those given by the usual assigned value method. Based on fitting a model to the funnel plot, we discuss a method for random-effects sensitivity analysis that deals with the problems of heterogeneity and publication bias. A meta-analysis of epidemiological studies on the effect of alcohol on the risk of breast cancer is used to illustrate the method. Our analysis suggests that the rate of increase in risk with alcohol consumption is substantially less than has been previously suggested. Copyright 2004 John Wiley & Sons, Ltd.

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Year:  2004        PMID: 14695636     DOI: 10.1002/sim.1595

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  13 in total

1.  Meta-analysis for linear and nonlinear dose-response relations: examples, an evaluation of approximations, and software.

Authors:  Nicola Orsini; Ruifeng Li; Alicja Wolk; Polyna Khudyakov; Donna Spiegelman
Journal:  Am J Epidemiol       Date:  2011-12-01       Impact factor: 4.897

2.  Empirical evaluation of meta-analytic approaches for nutrient and health outcome dose-response data.

Authors:  Winifred W Yu; Christopher H Schmid; Alice H Lichtenstein; Joseph Lau; Thomas A Trikalinos
Journal:  Res Synth Methods       Date:  2013-09       Impact factor: 5.273

3.  Flexible meta-regression to assess the shape of the benzene-leukemia exposure-response curve.

Authors:  Jelle Vlaanderen; Lützen Portengen; Nathaniel Rothman; Qing Lan; Hans Kromhout; Roel Vermeulen
Journal:  Environ Health Perspect       Date:  2009-11-18       Impact factor: 9.031

4.  A Bayesian dose-response meta-analysis model: A simulations study and application.

Authors:  Tasnim Hamza; Andrea Cipriani; Toshi A Furukawa; Matthias Egger; Nicola Orsini; Georgia Salanti
Journal:  Stat Methods Med Res       Date:  2021-01-27       Impact factor: 3.021

5.  Multivariate meta-analysis for non-linear and other multi-parameter associations.

Authors:  A Gasparrini; B Armstrong; M G Kenward
Journal:  Stat Med       Date:  2012-07-16       Impact factor: 2.373

6.  Clinical prediction of incident heart failure risk: a systematic review and meta-analysis.

Authors:  Hong Yang; Kazuaki Negishi; Petr Otahal; Thomas H Marwick
Journal:  Open Heart       Date:  2015-04-10

7.  The role of adiponectin in breast cancer: a meta-analysis.

Authors:  Li-Yuan Liu; Meng Wang; Zhong-Bing Ma; Li-Xiang Yu; Qiang Zhang; De-Zong Gao; Fei Wang; Zhi-Gang Yu
Journal:  PLoS One       Date:  2013-08-22       Impact factor: 3.240

8.  Multivariate meta-analysis of prognostic factor studies with multiple cut-points and/or methods of measurement.

Authors:  Richard D Riley; Eleni G Elia; Gemma Malin; Karla Hemming; Malcolm P Price
Journal:  Stat Med       Date:  2015-04-29       Impact factor: 2.373

9.  Sequential change detection and monitoring of temporal trends in random-effects meta-analysis.

Authors:  Samson Henry Dogo; Allan Clark; Elena Kulinskaya
Journal:  Res Synth Methods       Date:  2016-12-08       Impact factor: 5.273

10.  Synthesis of clinical prediction models under different sets of covariates with one individual patient data.

Authors:  Daisuke Yoneoka; Masayuki Henmi; Norie Sawada; Manami Inoue
Journal:  BMC Med Res Methodol       Date:  2015-11-19       Impact factor: 4.615

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