Comparison of logistic-regression based methods for simple mediation analysis with a dichotomous outcome variable

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Abstract

BACKGROUND: Logistic regression is often used for mediation analysis with a dichotomous outcome. However, previous studies showed that the indirect effect and proportion mediated are often affected by a change of scales in logistic regression models. To circumvent this, standardization has been proposed. The aim of this study was to show the relative performance of the unstandardized and standardized estimates of the indirect effect and proportion mediated based on multiple regression, structural equation modeling, and the potential outcomes framework for mediation models with a dichotomous outcome. METHODS: We compared the performance of the effect estimates yielded by the three methods using a simulation study and two real-life data examples from an observational cohort study (n = 360). RESULTS: Lowest bias and highest efficiency were observed for the estimates from the potential outcomes framework and for the crude indirect effect ab and the proportion mediated ab/(ab + c') based on multiple regression and SEM. CONCLUSIONS: We advise the use of either the potential outcomes framework estimates or the ab estimate of the indirect effect and the ab/(ab + c') estimate of the proportion mediated based on multiple regression and SEM when mediation analysis is based on logistic regression. Standardization of the coefficients prior to estimating the indirect effect and the proportion mediated may not increase the performance of these estimates.
LanguageEnglish
Pages19
JournalBMC Medical Research Methodology
Volume19
Issue number1
DOIs
Publication statusPublished - 2019

Cite this

@article{130bd6d907b24d4893871c17e8074d64,
title = "Comparison of logistic-regression based methods for simple mediation analysis with a dichotomous outcome variable",
abstract = "BACKGROUND: Logistic regression is often used for mediation analysis with a dichotomous outcome. However, previous studies showed that the indirect effect and proportion mediated are often affected by a change of scales in logistic regression models. To circumvent this, standardization has been proposed. The aim of this study was to show the relative performance of the unstandardized and standardized estimates of the indirect effect and proportion mediated based on multiple regression, structural equation modeling, and the potential outcomes framework for mediation models with a dichotomous outcome. METHODS: We compared the performance of the effect estimates yielded by the three methods using a simulation study and two real-life data examples from an observational cohort study (n = 360). RESULTS: Lowest bias and highest efficiency were observed for the estimates from the potential outcomes framework and for the crude indirect effect ab and the proportion mediated ab/(ab + c') based on multiple regression and SEM. CONCLUSIONS: We advise the use of either the potential outcomes framework estimates or the ab estimate of the indirect effect and the ab/(ab + c') estimate of the proportion mediated based on multiple regression and SEM when mediation analysis is based on logistic regression. Standardization of the coefficients prior to estimating the indirect effect and the proportion mediated may not increase the performance of these estimates.",
author = "Rijnhart, {Judith J. M.} and Twisk, {Jos W. R.} and Iris Eekhout and Heymans, {Martijn W.}",
year = "2019",
doi = "10.1186/s12874-018-0654-z",
language = "English",
volume = "19",
pages = "19",
journal = "BMC Medical Research Methodology",
issn = "1471-2288",
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TY - JOUR

T1 - Comparison of logistic-regression based methods for simple mediation analysis with a dichotomous outcome variable

AU - Rijnhart, Judith J. M.

AU - Twisk, Jos W. R.

AU - Eekhout, Iris

AU - Heymans, Martijn W.

PY - 2019

Y1 - 2019

N2 - BACKGROUND: Logistic regression is often used for mediation analysis with a dichotomous outcome. However, previous studies showed that the indirect effect and proportion mediated are often affected by a change of scales in logistic regression models. To circumvent this, standardization has been proposed. The aim of this study was to show the relative performance of the unstandardized and standardized estimates of the indirect effect and proportion mediated based on multiple regression, structural equation modeling, and the potential outcomes framework for mediation models with a dichotomous outcome. METHODS: We compared the performance of the effect estimates yielded by the three methods using a simulation study and two real-life data examples from an observational cohort study (n = 360). RESULTS: Lowest bias and highest efficiency were observed for the estimates from the potential outcomes framework and for the crude indirect effect ab and the proportion mediated ab/(ab + c') based on multiple regression and SEM. CONCLUSIONS: We advise the use of either the potential outcomes framework estimates or the ab estimate of the indirect effect and the ab/(ab + c') estimate of the proportion mediated based on multiple regression and SEM when mediation analysis is based on logistic regression. Standardization of the coefficients prior to estimating the indirect effect and the proportion mediated may not increase the performance of these estimates.

AB - BACKGROUND: Logistic regression is often used for mediation analysis with a dichotomous outcome. However, previous studies showed that the indirect effect and proportion mediated are often affected by a change of scales in logistic regression models. To circumvent this, standardization has been proposed. The aim of this study was to show the relative performance of the unstandardized and standardized estimates of the indirect effect and proportion mediated based on multiple regression, structural equation modeling, and the potential outcomes framework for mediation models with a dichotomous outcome. METHODS: We compared the performance of the effect estimates yielded by the three methods using a simulation study and two real-life data examples from an observational cohort study (n = 360). RESULTS: Lowest bias and highest efficiency were observed for the estimates from the potential outcomes framework and for the crude indirect effect ab and the proportion mediated ab/(ab + c') based on multiple regression and SEM. CONCLUSIONS: We advise the use of either the potential outcomes framework estimates or the ab estimate of the indirect effect and the ab/(ab + c') estimate of the proportion mediated based on multiple regression and SEM when mediation analysis is based on logistic regression. Standardization of the coefficients prior to estimating the indirect effect and the proportion mediated may not increase the performance of these estimates.

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UR - https://www.ncbi.nlm.nih.gov/pubmed/30665353

U2 - 10.1186/s12874-018-0654-z

DO - 10.1186/s12874-018-0654-z

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