vif.lme: Variance Inflation Factors for Mixed Models

In gmonette/spida15: Collection of miscellaneous functions for mixed models etc. prepared for SPIDA 2009+ (development version)

Description

Calculates versions of the variance-inflation and generalized variance-inflation factors for mixed models.

Usage

vif.lme(mod)

Arguments

mod

Details

The concept of Variance Inflation in linear models can be applied to mixed models in a number of ways since the variance-covariance matrix of the estimated fixed coefficients is not simply proportional to the inverse of the cross-product matrix for the data. This method for the generic function vif in the car package, implements the version based on the variance-covariance funtion of the estimated fixed coefficients. Since the vcov method is available for lm objects and lme objects, uses the code for the lm method for lme objects.

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (mod) 
{
    if (any(is.na(fixef(mod)))) 
        stop("there are aliased coefficients in the model")
    v <- vcov(mod)
    mm <- model.matrix(formula(mod), mod$data)
    assign <- attributes(mm)$assign
    if (names(fixef(mod)[1]) == "(Intercept)") {
        v <- v[-1, -1]
        assign <- assign[-1]
    }
    else warning("No intercept: vifs may not be sensible.")
    terms <- labels(terms(mod))
    n.terms <- length(terms)
    if (n.terms < 2) 
        stop("model contains fewer than 2 terms")
    R <- cov2cor(v)
    detR <- det(R)
    result <- matrix(0, n.terms, 3)
    rownames(result) <- terms
    colnames(result) <- c("GVIF", "Df", "GVIF^(1/2Df)")
    for (term in 1:n.terms) {
        subs <- which(assign == term)
        result[term, 1] <- det(as.matrix(R[subs, subs])) * det(as.matrix(R[-subs, 
            -subs]))/detR
        result[term, 2] <- length(subs)
    }
    if (all(result[, 2] == 1)) 
        result <- result[, 1]
    else result[, 3] <- result[, 1]^(1/(2 * result[, 2]))
    result
  }

gmonette/spida15 documentation built on May 17, 2019, 7:26 a.m.