Bivariate Association 2 - Continuous Variables and Categorical Variables

Overview

In this session students will learn statistical tests that applied to three groups. Students will be introduced to tests of continuous variables when the data is normally distributed or not normally distributed. In addition, students will learn tests suitable for proportion.

Summary

  • Analysis of variance: Is a test to determine whether any differences exist among two or more groups of subjects on one or more factors.
  • Kruskal-Wallis one-way ANOVA: A nonparametric test for comparing three or more of ordinal data or with numerical observations that are not normally distributed z approximation: Test of the equality of two independent proportions.
  • Chi-square test: The test of the null hypothesis that proportions are equal, or equivalently, that factors or characteristics are independent or not associated.
  • Fisher’s exact test: An exact test for 2 x 2 contingency table. It is used when the sample size is too small to use a chi-square test.
  • Relative risk: The ratio of the incidence of a given disease in exposed to the incidence of the disease in the unexposed.
  • Odds ratio: An estimate of relative risk in case-control studies. It is the odds that a patient was exposed to a given risk factor divided by the odds that a control was exposed to a given risk factor.
  • Cochran-Armitage trend test: Is a test of linear trend in proportions.

Additional Reading

Test of Statistical Significance

Chapter 11: Bivariate Analysis