psglm is used to fit generalized linear models to the verification process. This function requires a symbolic formula of the linear predictor, and a specified regression model.
Usage
psglm(formula, data, model = "logit", test = FALSE, trace = TRUE, ...)
Value
psglm returns a list containing the following components:
coeff
a vector of estimated coefficients.
values
fitted values of the model.
Hess
the Hessian of the measure of fit at the estimated coefficients.
x
a design model matrix.
formula
the formula supplied.
model
the model object used.
Arguments
formula
an object of class "formula": a symbolic description of the model to be fitted.
data
an optional data frame containing the variables in the model.
model
a specified model to be used in the fitting. The suggestion regression models are logit, probit and threshold. If model is ignored, then psglm use a default model as logit.
test
a logical value indicating whether p-values of the regression coefficients should be returned.
trace
switch for tracing estimation process. Default TRUE.
...
optional arguments to be passed to glm.
Details
psglm estimates the verification probabilities of the patients. The suggestion model is designed as a list containing: logit, probit and threshold.