Implements the criterion-related profile analysis described in Davison & Davenport (2002).
An object of class
An optional data frame, list or environment containing the variables in the model.
Corresponds to the scalar constant and must be greater than 0. Defaults to 100.
How should missing data be handled? Function defaults to failing if missing data are present.
A description of the error distribution and link function to be used in the model. See
An option vector of weights to be used in the fitting process.
cpa function requires two arguments: criterion and predictors. The function returns the criterion-related
profile analysis described in Davison & Davenport (2002). Missing data are presently handled by specifying
na.action = "na.omit", which performs listwise deletion and
na.action = "na.fail", the default,
which causes the function to fail. The following S3 generic functions are available:
plot(). These functions provide a summary of the analysis (namely, R2 and the level a
nd pattern components); perform ANOVA of the R2 for the pattern, the level, and the overall model; provide
output similar to
lm(), and plots the pattern effect.
An object of class
critpat is returned, listing the following components:
lvl.comp - the level component
pat.comp - the pattern component
b - the unstandardized regression weights
bstar - the mean centered regression weights
xc - the scalar constant times bstar
k - the scale constant
Covpc - the pattern effect
Ypred - the predicted values
r2 - the proportion of variability attributed to the different components
F.table - the associated F-statistic table
F.statistic - the F-statistics
df - the df used in the test
pvalue - the p-values for the test
Davison, M., & Davenport, E. (2002). Identifying criterion-related patterns of predictor scores using multiple regression. Psychological Methods, 7(4), 468-484. DOI: 10.1037/1082-989X.7.4.468.
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