Statistical techniques for juror and jury research

Authors


Correspondence should be addressed to Professor Daniel B. Wright, Department of Psychology, Florida International University, Miami, FL 33199, USA (e-mail: dwright@fiu.edu).

Abstract

Juror and jury research is a thriving area of investigation in legal psychology. The basic ANOVA and regression, well-known by psychologists, are inappropriate for analysing many types of data from this area of research. This paper describes statistical techniques suitable for some of the main questions asked by jury researchers. First, we discuss how to examine manipulations that may affect levels of reasonable doubt and how to measure reasonable doubt using the coefficients estimated from a logistic regression. Second, we compare models designed for analysing the data like those which often arise in research where jurors first make categorical judgments (e.g., negligent or not, guilty or not) and then dependent on their response may make another judgment (e.g., award, punishment). We concentrate on zero-inflated and hurdle models. Third, we examine how to take into account that jurors are part of a jury using multilevel modelling. We illustrate each of the techniques using software that can be downloaded for free from the Internet (the package R) and provide a web page that gives further details for running these analyses.

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