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Re-expressing coefficients from regression models for inclusion in a meta-analysis.
Linakis, Matthew W; Van Landingham, Cynthia; Gasparini, Alessandro; Longnecker, Matthew P.
Afiliação
  • Linakis MW; Ramboll U.S. Consulting, Raleigh, NC, 27612, USA, 3214 Charles B Root Wynd #130. mlinakis@ramboll.com.
  • Van Landingham C; Ramboll U.S. Consulting, Monroe, LA, 71201, USA.
  • Gasparini A; Red Door Analytics AB, Stockholm, Sweden.
  • Longnecker MP; Ramboll U.S. Consulting, Raleigh, NC, 27612, USA, 3214 Charles B Root Wynd #130.
BMC Med Res Methodol ; 24(1): 6, 2024 01 08.
Article em En | MEDLINE | ID: mdl-38191310
ABSTRACT
Meta-analysis poses a challenge when original study results have been expressed in a non-uniform manner, such as when regression results from some original studies were based on a log-transformed key independent variable while in others no transformation was used. Methods of re-expressing regression coefficients to generate comparable results across studies regardless of data transformation have recently been developed. We examined the relative bias of three re-expression methods using simulations and 15 real data examples where the independent variable had a skewed distribution. Regression coefficients from models with log-transformed independent variables were re-expressed as though they were based on an untransformed variable. We compared the re-expressed coefficients to those from a model fit to the untransformed variable. In the simulated and real data, all three re-expression methods usually gave biased results, and the skewness of the independent variable predicted the amount of bias. How best to synthesize the results of the log-transformed and absolute exposure evidence streams remains an open question and may depend on the scientific discipline, scale of the outcome, and other considerations.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article