ipdmeta-class: Class for representing ipdlme objects

In ipdmeta: Tools for subgroup analyses with multiple trial data using aggregate statistics

Description

The ipdlme class represents the fit of a linear mixed-effects model of individual patient data meta-analysis of multiple parallel group clinical trials, based on aggregate data estimation methods.

Objects from the Class

Objects can be created by calls of the form new("ipdlme", ...) or via the function ipdlme.

Slots

The class "ipdlme" represents a linear mixed model to assess effect modification of multiple clinical trials and contains the slots:

fixef:

The vector of the population effect estimates.

ranef:

The matrix of the study-specific intercept and treatment random effects.

vcov.fixef:

The variance-covariance matrix for inference with the population effects.

vcov.ranef:

The variance-covariance matrix for inference with the study random effects.

sigma2:

Estimate of the residual variance.

VarCorr:

Covariance-variance matrix for bivariate normal random effects.

convergence.trace:

A list of the values of each of the effects and variance components at each iteration in the maximization algorith.

converged:

Logical value indicating whether the convergence criterion was met.

n.iter:

The total number of iterations used in the optimization algorithm.

max.iter:

The maximum number of iterations specified for the optimization algorithm.

tol:

The tolerance level on which the termination rule for convergence is based.

df:

The degrees of freedom of the model fit.

Methods

The following methods are extractors for the component that shares the method's name:

fixef

signature(object = "ipdlme")

ranef

signature(object = "ipdlme")

coef

signature(object = "ipdlme")

vcov

signature(object = "ipdlme")

Var

signature(object = "ipdlme")

sigma2

signature(object = "ipdlme")

vcov.fixef

signature(object = "ipdlme")

vcov.ranef

signature(object = "ipdlme")

convergence

signature(object = "ipdlme")

converged

signature(object = "ipdlme")

n.iter

signature(object = "ipdlme")

tol

signature(object = "ipdlme")

max.iter

signature(object = "ipdlme")

print

signature(x = "ipdlme"): print information about the fitted model.

show

signature(object = "ipdlme"): Same as the print method.

confint

signature(object = "ipdlme",parm, level = 0.95, ...)Returns the specified confidence interval for all the population parameters.

plot

signature(x = "ipdlme",y,...): Displays a forest plot of the study intercept and treatment effects with the option of user-defined labels for the studies.

summary

signature(object = "ipdlme"):Summary table of standard error and Wald tests for the population effects. A list of the study random effects and estimates of the variance components are also displayed.

See Also

ipdlme

Examples

data(regress_chol)

metafit <- ipdlme(n,Y,S2)

converged(metafit)

summary(metafit)

confint(metafit)

ipdmeta documentation built on May 2, 2019, 3:29 p.m.