title: An introduction to logistic regression: from basic concepts to interpretation with particular attention to nursing domain.
abstract: OBJECTIVE
  The purpose of this article is twofold: 1) introducing logistic regression (LR), a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, and 2) examining use and reporting of LR in the nursing literature.
  
  
  METHODS
  Text books on LR and research articles employing LR as main statistical analysis were reviewed. Twenty-three articles published between 2010 and 2011 in the Journal of Korean Academy of Nursing were analyzed for proper use and reporting of LR models.
  
  
  RESULTS
  Logistic regression from basic concepts such as odds, odds ratio, logit transformation and logistic curve, assumption, fitting, reporting and interpreting to cautions were presented. Substantial shortcomings were found in both use of LR and reporting of results. For many studies, sample size was not sufficiently large to call into question the accuracy of the regression model. Additionally, only one study reported validation analysis.
  
  
  CONCLUSIONS
  Nursing researchers need to pay greater attention to guidelines concerning the use and reporting of LR models.
authors.affiliation: College of Nursing and System Biomedical Informatics National Core Research Center, Seoul National University, Seoul, Korea. hapark@snu.ac.kr
authors.forename: Hyeoun Ae
authors.initials: HA
authors.lastname: Park
mesh_terms: D006801:Humans; D016015:Logistic Models; D015233:Models, Statistical; D016017:Odds Ratio; D011643:Publishing / Q000592:standards; D012106:Research
keywords: Logit function; Maximum likelihood estimation; Odds; Odds ratio; Wald test