Regression models: Calculating the confidence interval of effects in the presence of interactions

Adolfo Figueiras, Jose Maria Domenech-Massons, Carmen Cadarso

Research output: Contribution to journalArticleResearchpeer-review

65 Citations (Scopus)

Abstract

The main goal of regression analysis (multiple, logistic, Cox) is to assess the relationship of one or more exposure variables to a response variable, in the presence of confounding and interaction. The confidence interval for the regression coefficient of the exposure variable, obtained through the use of a computer statistical package, quantify these relationships for models without interaction. Relationships between variables that present interactions are represented by two or more terms, and the corresponding confidence intervals can be calculated 'manually' from the covariance matrix. This paper suggests an easy procedure for obtaining confidence intervals from any statistical package. This procedure is applicable for modifying variables which are continuous as well as categorical.
Original languageEnglish
Pages (from-to)2099-2105
JournalStatistics in Medicine
Volume17
Issue number18
DOIs
Publication statusPublished - 30 Sep 1998

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