Number of covariate effect parameters. This is defined as the number of covariates on misclassification (with factors expanded as contrasts) multiplied by the number of allowed misclassifications in the model.

Number of distinct covariate effect parameters, as npars, but after any equality constraints have been applied.

Number of covariates on misclassification, with factors expanded as contrasts.

List of equality constraints on these covariate effects, as supplied in the miscconstraint argument to msm.

Names / labels of these covariates in the model matrix (see model.matrix.msm).

Initial values for these covariate effects, as a vector formed from the misccovinits list supplied to msm.

Means of these covariates in the data (excluding data not required to fit the model, such as observations with missing data in other elements or subjects' last observations). This includes means of 0/1 factor contrasts as well as continuous covariates (for historic reasons, which may not be sensible).