Analysis of Categorical Data

5 Analysis of Categorical DataPeople like to clump things into categories. Virtually every researchproject categorizes some of its observations into neat, little distinct bins:male or female; marital status; broken or not broken; small, medium, orlarge; race of patient; with or without a tonsillectomy; and so on. When wecollect data by categories, we record counts how many observations fallinto a particular bin. Categorical variables are usually classified as being oftwo basic types: nominal and ordinal. Nominal variables involve categoriesthat have no particular order such as hair color, race, or clinic site, while thecategories associated with an ordinal variable have some inherent ordering(categories of socioeconomic status, etc.). Unless otherwise stated, the pro-cedures discussed here can be used on any type of Categorical data. There aresome specific procedures for ordinal data, and they will be briefly discussedlater in the have devised a number of ways to analyze and explaincategorical data.

• McNemar’s test is designed for the analysis of paired dichotomous, categori-cal variables to detect disagreement or change. • The Mantel-Haenszel test is used to determine whether there is a relationship between two dichotomous variables controlling for or within levels of a third variable. 113 05-Elliott-4987.qxd 7/18/2006 5:26 PM Page 113

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