| dfSigma {lavaSearch2} | R Documentation |
Degree of Freedom for the Chi-Square Test
Description
Computation of the degrees of freedom of the chi-squared distribution relative to the model-based variance
Usage
dfSigma(contrast, score, vcov, rvcov, dVcov, dRvcov, keep.param, type)
Arguments
contrast |
[numeric vector] the linear combination of parameters to test |
score |
[numeric matrix] the individual score for each parameter. |
vcov |
[numeric matrix] the model-based variance-covariance matrix of the parameters. |
rvcov |
[numeric matrix] the robust variance-covariance matrix of the parameters. |
dVcov |
[numeric array] the first derivative of the model-based variance-covariance matrix of the parameters. |
dRvcov |
[numeric array] the first derivative of the robust variance-covariance matrix of the parameters. |
keep.param |
[character vector] the name of the parameters with non-zero first derivative of their variance parameter. |
type |
[integer] 1 corresponds to the Satterthwaite approximation of the the degrees of freedom applied to the model-based variance, 2 to the Satterthwaite approximation of the the degrees of freedom applied to the robust variance, 3 to the approximation described in (Pan, 2002) section 2 and 3.1. |
References
Wei Pan and Melanie M. Wall, Small-sample adjustments in using the sandwich variance estiamtor in generalized estimating equations. Statistics in medicine (2002) 21:1429-1441.