The Chi-Square Test: Often Used and More Often Misinterpreted

Autor/inn/en	Franke, Todd Michael; Ho, Timothy; Christie, Christina A.
Titel	The Chi-Square Test: Often Used and More Often Misinterpreted
Quelle	In: American Journal of Evaluation, 33 (2012) 3, S.448-458 (11 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1098-2140
DOI	10.1177/1098214011426594
Schlagwörter	Evaluators; Statistical Analysis; Research Methodology; Evaluation Research; Data Analysis; Misconceptions; Incidence; Goodness of Fit; Comparative Analysis; Sampling + Suchen Sie Ihr Suchwort? Statistische Analyse; Research method; Forschungsmethode; Evaluationsforschung; Auswertung; Missverständnis; Vorkommen
Abstract	The examination of cross-classified category data is common in evaluation and research, with Karl Pearson's family of chi-square tests representing one of the most utilized statistical analyses for answering questions about the association or difference between categorical variables. Unfortunately, these tests are also among the more commonly misinterpreted statistical tests in the field. The problem is not that researchers and evaluators misapply the results of chi-square tests, but rather they tend to over interpret or incorrectly interpret the results, leading to statements that may have limited or no statistical support based on the analyses preformed. This paper attempts to clarify any confusion about the uses and interpretations of the family of chi-square tests developed by Pearson, focusing primarily on the chi-square tests of independence and homogeneity of variance (identity of distributions). A brief survey of the recent evaluation literature is presented to illustrate the prevalence of the chi-square test and to offer examples of how these tests are misinterpreted.While the omnibus form of all three tests in the Karl Pearson family of chi-square tests--independence, homogeneity, and goodness-of-fit,--use essentially the same formula, each of these three tests is, in fact, distinct with specific hypotheses, sampling approaches, interpretations, and options following rejection of the null hypothesis. Finally, a little known option, the use and interpretation of post hoc comparisons based on Goodman's procedure (Goodman, 1963) following the rejection of the chi-square test of homogeneity, is described in detail. (Contains 5 tables and 4 notes.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10