Applied researchers have employed chi-square tests for more than one hundred years. This paper addresses the question of how one should follow a statistically significant chi-square test result in order to determine the source of that result. Four approaches were evaluated: calculating residuals, comparing cells, ransacking, and partitioning. Data from two recent journal articles were used to illustrate these approaches. A call is made for greater consideration of foundational techniques such as the chi-square tests. Accessed 74,155 times on https://pareonline.net from April 06, 2015 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.
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"Chi-Square Test is Statistically Significant: Now What?,"
Practical Assessment, Research, and Evaluation: Vol. 20
, Article 8.
Available at: https://scholarworks.umass.edu/pare/vol20/iss1/8