Logistic Regression and Related Methods

Márcio A. Diniz () and Tiago M. Magalhães
Additional contact information
Márcio A. Diniz: Samuel Oschin Cancer Center, Cedars Sinai Medical Center, Biostatistics and Bioinfomatics Research Center
Tiago M. Magalhães: Institute of Exact Sciences, Federal University of Juiz de Fora, Department of Statistics

Chapter 91 in Principles and Practice of Clinical Trials, 2022, pp 1789-1811 from Springer

Abstract: Abstract Inference on binary outcomes is a common goal in clinical trials and case-control studies. Logistic regression is the usual approach to estimate treatment effect adjusted for categorical and continuous confounding variables. In this chapter, model building, interpretation of parameters, diagnostics, and inference to small sample sizes are discussed. At last, a case study is presented applying the proposed analytic strategies.

Keywords: Binary response; Odds ratio; Case-control study; Cohort studies (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-52636-2_122

Ordering information: This item can be ordered from
http://www.springer.com/9783319526362

DOI: 10.1007/978-3-319-52636-2_122

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().