The proper application of logistic regression model in complex survey data: a systematic review.

ABSTRACT:

Background

Logistic regression is a useful statistical technique commonly used in many fields like healthcare, marketing, or finance to generate insights from binary outcomes (e.g., sick vs. not sick). However, when applying logistic regression to complex survey data, which includes complex sampling designs, specific methodological issues are often overlooked.

Methods

The systematic review extensively searched the PubMed and ScienceDirect databases from January 2015 to December 2021, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, focusing primarily on the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). 810 articles met the inclusion criteria and were included in the analysis. When

SUBMITTER: Dey D 

PROVIDER: S-EPMC11752662 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature