Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio

Clicks: 653
ID: 270768
2003
Free PDF
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Cox or Poisson regression with robust variance and log-binomial regression provide correct estimates and are a better alternative for the analysis of cross-sectional studies with binary outcomes than logistic regression, since the prevalence ratio is more interpretable and easier to communicate to n …
Reference Key
aj2003bmcalternatives Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Barros AJ;Hirakata VN;;
Journal BMC medical research methodology
Year 2003
DOI
DOI not found
URL
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=14567763
Keywords
National Center for Biotechnology Information NCBI NLM MEDLINE humans pubmed abstract nih national institutes of health national library of medicine logistic models models research support non-u.s. gov't Comparative Study linear models Evaluation Study Proportional Hazards Models odds ratio statistical* prevalence empirical research pmid:14567763 pmc521200 doi:10.1186/1471-2288-3-21 aluísio j d barros vânia n hirakata cross-sectional studies* poisson distribution

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.