pim {anoint} | R Documentation |
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 |
exact |
logical indicator whether |
interval |
interval passed to |
n.boot |
number of bootstrap resamples for variance calculations |
... |
other arguments passed to |
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
.
Value
Returns instance of pim
class.
Author(s)
Stephanie Kovalchik <s.a.kovalchik@gmail.com>
References
Follmann DA, Proschan MA. A multivariate test of interaction for use in clinical trials. Biometrics 1999; 55(4):1151-1155
See Also
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)