title: Parametric methods outperformed non-parametric methods in comparisons of discrete numerical variables.
abstract: BACKGROUND
  The number of events per individual is a widely reported variable in medical research papers. Such variables are the most common representation of the general variable type called discrete numerical. There is currently no consensus on how to compare and present such variables, and recommendations are lacking. The objective of this paper is to present recommendations for analysis and presentation of results for discrete numerical variables.
  
  
  METHODS
  Two simulation studies were used to investigate the performance of hypothesis tests and confidence interval methods for variables with outcomes {0, 1, 2}, {0, 1, 2, 3}, {0, 1, 2, 3, 4}, and {0, 1, 2, 3, 4, 5}, using the difference between the means as an effect measure.
  
  
  RESULTS
  The Welch U test (the T test with adjustment for unequal variances) and its associated confidence interval performed well for almost all situations considered. The Brunner-Munzel test also performed well, except for small sample sizes (10 in each group). The ordinary T test, the Wilcoxon-Mann-Whitney test, the percentile bootstrap interval, and the bootstrap-t interval did not perform satisfactorily.
  
  
  CONCLUSIONS
  The difference between the means is an appropriate effect measure for comparing two independent discrete numerical variables that has both lower and upper bounds. To analyze this problem, we encourage more frequent use of parametric hypothesis tests and confidence intervals.
authors.affiliation: Unit of Biostatistics and Epidemiology, Oslo University Hospital, Norway. morten.fagerland@medisin.uio.no
authors.forename: Morten W
authors.initials: MW
authors.lastname: Fagerland
authors.forename: Leiv
authors.initials: L
authors.lastname: Sandvik
authors.forename: Petter
authors.initials: P
authors.lastname: Mowinckel
mesh_terms: D003198:Computer Simulation; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D005260:Female; D017408:Guidelines as Topic; D006801:Humans; D008297:Male; D015233:Models, Statistical; D010353:Patient Education as Topic; D016032:Randomized Controlled Trials as Topic; D018709:Statistics, Nonparametric