Choosing an Appropriate Real-Life Measure of Effect Size: The Case of a Continuous Predictor and a Binary Outcome

Abstract

A case study of data on age and pregnancy is used to point up some morals for practicing data analysts, including the superiority of regression over t tests, exploratory scatterplot smoothing as a key method of checking form of relationship, and the value of logistic regression followed by adjust as a way of getting at the numbers of most interest.