| Log-Linear Models |
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One basic and straightforward method for analyzing data is via crosstabulation. For example, a medical researcher may tabulate the frequency of different symptoms by patients' age and gender; an educational researcher may tabulate the number of high school drop-outs by age, gender, and ethnic background; an economist may tabulate the number of business failures by industry, region, and initial capitalization; a market researcher may tabulate consumer preferences by product, age, and gender; etc. In all of these cases, the major results of interest can be summarized in a multi-way frequency table, that is, in a crosstabulation table with two or more factors.
Log-Linear provides a more "sophisticated" way of looking at crosstabulation tables. Specifically, you can test the different factors that are used in the crosstabulation (e.g., gender, region, etc.) and their interactions for statistical significance. Correspondence analysis is a descriptive/exploratory technique designed to analyze two-way and multi-way tables containing some measure of correspondence between the rows and columns. The results provide information which is similar in nature to those produced by Factor Analysis techniques, and they allow one to explore the structure of the categorical variables included in the table. |