Multilevel modelling for measuring interaction of effects between multiple categorical variables: An illustrative application using risk factors for preeclampsia.

ABSTRACT:

Background

Measuring multiple and higher-order interaction effects between multiple categorical variables proves challenging.

Objectives

To illustrate a multilevel modelling approach to studying complex interactions.

Methods

We apply a two-level random-intercept linear regression to a binary outcome for individuals (level-1) nested within strata (level-2) defined by all observed combinations of multiple categorical exposure variables. As a pedagogic application, we analyse 36 strata defined by five risk factors of preeclampsia (parity, previous preeclampsia, chronic hypertension, multiple pregnancies, body mass index category) among 652,603 women in the Swedish Medical Birth Registry between 2002 and 2010.

Results

The absolute risk of preeclampsia was 4% but wa

SUBMITTER: Rodriguez-Lopez M 

PROVIDER: S-EPMC10098842 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature