The possible benefits of reporting percentage point effects

Abstract

Many academic researchers regard logistic regression as the preeminent analytic approach for modeling binary outcomes. It can identify and estimate the effects of actions to increase or decrease the size or proportion of the group of interest. It can also predict each case’s probability of belonging to one group instead of another, given the model’s explanatory variables. However, evidence indicates that market researchers do not use it extensively to analyze survey data, partly because of the difficulty in translating logistic regression’s standard analysis output—logits, odds, and odds ratios—into clear, action-oriented findings and recommendations. The aim here is to offer an informed view, supported by analysis of Pew Research Center survey data, of the possible benefits of reporting percentage point effects (e.g., a one-unit change in x is associated with a three-percentage-point increase in y, all else being equal), in addition to logits, odds, and odds ratios. Such reporting may help to reduce any gap between what some clients expect—particularly when they ask researchers to identify and estimate the effects of actions for increasing or decreasing a critical group’s size or proportion—and what they may receive in return. It may also create new consulting and relationship-building opportunities for market researchers.