Bayesian Survey Analysis: Introduction

Walter R. Paczkowski
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Walter R. Paczkowski: Data Analytics Corp.

Chapter Chapter 8 in Modern Survey Analysis, 2022, pp 251-302 from Springer

Abstract: Abstract I previously discussed and illustrated deep analysis methods for survey data when the target variable of a Core Question is measured on a continuous or discrete scale. A prominent method is OLS regression for a continuous target. The target is the dependent or left-hand-side variable, and the independent variables, or features (perhaps from Surround Questions such as demographics), are the right-hand-side variables in a linear model. A logit model is used rather than an OLS model for a discrete target because of statistical issues, the most important being that OLS can predict outside the range of the target. For example, if the target is customer satisfaction measured on a 5-point Likert scale, but the five points are encoded as 0 and 1 (i.e., B3B and T2B, respectively), then OLS could predict a value of −2 for the binary target. What is −2? A logit model is used to avoid this nonsensical result. I illustrated how this is handled in Chap. 5 .

Date: 2022
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DOI: 10.1007/978-3-030-76267-4_8

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