Should we always choose a nonparametric test when comparing two apparently nonnormal distributions?

J Clin Epidemiol. 2001 Jan;54(1):86-92. doi: 10.1016/s0895-4356(00)00264-x.


When clinical data are subjected to statistical analysis, a common question is how to choose an appropriate significance test. Comparing two independent groups with observations measured on a continuous scale, the question is typically whether to choose the two-sample-t test or the Wilcoxon-Mann-Whitney test (WMW test). Similar results are often obtained, but which conclusion can be drawn if significance tests give highly different P-values? The t test is optimal for normally distributed observations with common variance and robust to deviations from normality if sample sizes are not very small. The WMW test makes no distributional assumptions, but depends heavily on equal shape and variance of the two distributions (homoscedasticity). We have compared the properties of the traditional two-sample t test, a modified t test allowing unequal variance, and the WMW test by stochastic simulation. All show acceptable behaviour when the two distributions have similar variance. When variances differ, the modified t test is superior to the other two.

Publication types

  • Comparative Study
  • Validation Study

MeSH terms

  • Analysis of Variance
  • Antineoplastic Combined Chemotherapy Protocols / therapeutic use
  • Combined Modality Therapy
  • Data Interpretation, Statistical*
  • Etoposide / therapeutic use
  • Granulocyte Colony-Stimulating Factor / therapeutic use
  • Hematopoietic Stem Cell Transplantation
  • Hodgkin Disease / blood
  • Hodgkin Disease / immunology
  • Hodgkin Disease / therapy
  • Humans
  • Ifosfamide / therapeutic use
  • Leukocyte Count
  • Lymphoma, Non-Hodgkin / blood
  • Lymphoma, Non-Hodgkin / immunology
  • Lymphoma, Non-Hodgkin / therapy
  • Methotrexate / therapeutic use
  • Mitoguazone / therapeutic use
  • Models, Statistical*
  • Neutrophils
  • Numerical Analysis, Computer-Assisted*
  • Sample Size
  • Software*
  • Statistical Distributions*
  • Statistics, Nonparametric*
  • Stochastic Processes
  • Time Factors


  • Granulocyte Colony-Stimulating Factor
  • Etoposide
  • Mitoguazone
  • Ifosfamide
  • Methotrexate

Supplementary concepts

  • MIME protocol