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Measuring and estimating the interaction between exposures on a dichotomous outcome for observational studies
Högskolan i Gävle, Akademin för teknik och miljö, Avdelningen för elektronik, matematik och naturvetenskap, Matematik.
Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
2017 (Engelska)Ingår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 44, nr 14, s. 2483-2498Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

In observational studies for the interaction between exposures on a dichotomous outcome of a certain population, usually one parameter of a regression model is used to describe the interaction, leading to one measure of the interaction. In this article we use the conditional risk of an outcome given exposures and covariates to describe the interaction and obtain five different measures of the interaction, that is, difference between the marginal risk differences, ratio of the marginal risk ratios, ratio of the marginal odds ratios, ratio of the conditional risk ratios, and ratio of the conditional odds ratios. These measures reflect different aspects of the interaction. By using only one regression model for the conditional risk, we obtain the maximum-likelihood (ML)-based point and interval estimates of these measures, which are most efficient due to the nature of ML. We use the ML estimates of the model parameters to obtain the ML estimates of these measures. We use the approximate normal distribution of the ML estimates of the model parameters to obtain approximate non-normal distributions of the ML estimates of these measures and then confidence intervals of these measures. The method can be easily implemented and is presented via a medical example.

Ort, förlag, år, upplaga, sidor
2017. Vol. 44, nr 14, s. 2483-2498
Nyckelord [en]
Interaction, interaction measure, point estimate, interval estimate, regression model
Nationell ämneskategori
Sannolikhetsteori och statistik
Identifikatorer
URN: urn:nbn:se:hig:diva-18760DOI: 10.1080/02664763.2016.1257587ISI: 000410837000002Scopus ID: 2-s2.0-84996537841OAI: oai:DiVA.org:hig-18760DiVA, id: diva2:780675
Tillgänglig från: 2015-01-14 Skapad: 2015-01-14 Senast uppdaterad: 2019-09-04Bibliografiskt granskad

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Wang, Xiaoqin

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