## File: vcovCR.robu.Rd

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r-cran-clubsandwich 0.5.3-1
 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869 % Generated by roxygen2: do not edit by hand % Please edit documentation in R/robu.R \name{vcovCR.robu} \alias{vcovCR.robu} \title{Cluster-robust variance-covariance matrix for a robu object.} \usage{ \method{vcovCR}{robu}(obj, cluster, type, target, inverse_var, form = "sandwich", ...) } \arguments{ \item{obj}{Fitted model for which to calculate the variance-covariance matrix} \item{cluster}{Optional expression or vector indicating which observations belong to the same cluster. If not specified, will be set to the \code{studynum} used in fitting the \code{\link[robumeta]{robu}} object.} \item{type}{Character string specifying which small-sample adjustment should be used, with available options \code{"CR0"}, \code{"CR1"}, \code{"CR1p"}, \code{"CR1S"}, \code{"CR2"}, or \code{"CR3"}. See "Details" section of \code{\link{vcovCR}} for further information.} \item{target}{Optional matrix or vector describing the working variance-covariance model used to calculate the \code{CR2} and \code{CR4} adjustment matrices. If not specified, the target is taken to be the inverse of the estimated weights used in fitting the \code{\link[robumeta]{robu}} object.} \item{inverse_var}{Optional logical indicating whether the weights used in fitting the model are inverse-variance. If not specified, \code{vcovCR} will attempt to infer a value.} \item{form}{Controls the form of the returned matrix. The default \code{"sandwich"} will return the sandwich variance-covariance matrix. Alternately, setting \code{form = "meat"} will return only the meat of the sandwich and setting \code{form = B}, where \code{B} is a matrix of appropriate dimension, will return the sandwich variance-covariance matrix calculated using \code{B} as the bread.} \item{...}{Additional arguments available for some classes of objects.} } \value{ An object of class \code{c("vcovCR","clubSandwich")}, which consists of a matrix of the estimated variance of and covariances between the regression coefficient estimates. } \description{ \code{vcovCR} returns a sandwich estimate of the variance-covariance matrix of a set of regression coefficient estimates from a \code{\link[robumeta]{robu}} object. } \examples{ library(robumeta) data(hierdat) robu_fit <- robu(effectsize ~ binge + followup + sreport + age, data = hierdat, studynum = studyid, var.eff.size = var, modelweights = "HIER") robu_fit robu_CR2 <- vcovCR(robu_fit, type = "CR2") robu_CR2 coef_test(robu_fit, vcov = robu_CR2, test = c("Satterthwaite", "saddlepoint")) Wald_test(robu_fit, constraints = constrain_zero(c(2,4)), vcov = robu_CR2) Wald_test(robu_fit, constraints = constrain_zero(2:5), vcov = robu_CR2) } \seealso{ \code{\link{vcovCR}} }