The use of general linear regression methods for
the analysis of categorical data is recommended.
The general linear model analysis of a 0,1 coded response
variable produces estimates of the same response
probabilities that might otherwise be estimated
from frequencies in a multiway contingency
table. When factors in the design are correlated,
the regression analysis estimates the same response
probabilities that would be estimated from the
simple marginal frequencies in a balanced orthogonal
design. The independent effects that are estimated
by the regression analysis are the unweighted
means of the response probabilities in
various cells of a cross-classification design; however,
it is not necessary that all cells in a complex
design be filled in order for the estimates to have
that interpretation. The advantages of the general
linear model analysis include familiarity of most
psychologists with the methods, availability of
computer programs, and ease of application to
problems that are too complex for development of
complete multiway contingency tables.
Overall, John E. (1980). Calculation of adjusted response frequencies using least squares regression methods. Applied Psychological Measurement, 4, 65-78. doi:10.1177/014662168000400108
Overall, John E..
Calculation of adjusted response frequencies using least squares regression methods.
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