anoint (version 1.4)

pim: Fit proportional interaction model

Description

Fits a proportional interactions model from parallel-group clinical trial.

Usage

pim(object,exact=TRUE,interval=c(-3,3),n.boot=NULL,...)

Arguments

object

object of class anoint

exact

logical indicator whether exact or approximate fit is performed

interval

interval passed to optimize if exact is TRUE

n.boot

number of bootstrap resamples for variance calculations

...

other arguments passed to optimize if exact is TRUE

Value

Returns instance of pim class.

Details

When exact is FALSE the method of Follmann and Proschan (1999) is used to estimate the PIM coefficients and perform a likelihood-ratio test on the responsiveness parameter theta.

If exact method is specified, then optimize is used to maximize the profile-likelihood alternating between fixing theta and fixing all other PIM parameters. The arguments interval and additional arguments to ... control the optimization with respect to theta.

When n.boot is NULL no bootstrap resamples are taken. In this case, when using the exact method the variance-covariance for the main effects is based on the model likelihood treating the responsiveness parameter as fixed. To include uncertainty measures for the responsiveness parameter, bootstrap resampling can be used. For the approximate method, only the bootstrap resampling variance is provided for the vcov and confint methods, which is invoked by specifying a positive integer number of samples or n.boot.

References

Follmann DA, Proschan MA. A multivariate test of interaction for use in clinical trials. Biometrics 1999; 55(4):1151-1155

See Also

pim-class

Examples

set.seed(1115)

pim.interaction <- data.anoint(
                             alpha = c(log(.2/.8),log(.2*.75/(1-.2*.75))),
                             beta = log(c(1.25,1.5)),
                             gamma = rep(1.2,2),
                             mean = c(0,0),
                             vcov = diag(2),
                             type="binomial", n = 500
                             )


object <- anoint(y~(V1+V2)*trt,data=pim.interaction,family="binomial")

object

fit <- pim(object)

fit

summary(fit)

# EXAMPLE WITH BOOTSTRAP 
fit <- pim(object, n=50)
summary(fit)
confint(fit)