ematrix.msm(x, covariates="mean", cl=0.95)msm"mean", denoting the means of the covariates in
the data (this is the default),
the number 0, indicatingematrix.msm presents estimates and confidence limits. To
present estimates and standard errors, do something like ematrix.msm(x)[c("estimates","SE")]
msm. A covariance matrix is estimated from the
Hessian of the maximised log-likelihood. From these, the delta method
is used to obtain standard errors of the probabilities on the natural
scale at arbitrary covariate values. Confidence intervals are
estimated by assuming normality on the logit scale.qmatrix.msm