psglm {bcROCsurface} | R Documentation |
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.
psglm(formula, data, model = "logit", test = FALSE, trace = TRUE, ...)
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 |
test |
a logical value indicating whether p-values of the regression coefficients should be returned. |
trace |
switch for tracing estimation process. Default |
... |
optional arguments to be passed to |
psglm
estimates the verification probabilities of the patients. The suggestion model is designed as a list containing: logit, probit and threshold.
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. |
data(EOC) out <- psglm(V ~ CA125 + CA153 + Age, data = EOC, test = TRUE)