Table 2.
Function(s) | Returns |
---|---|
logLik, AIC, BIC | the log-likelihood, Akaike information criterion and Bayesian information criterion statistics, respectively |
coef, fixef | the fixed effects parameter estimates |
ranef | the BLUPs (and optional standard errors) |
printa, summaryc | short and long model summary outputs, respectively |
fitted, resid | the fitted values and raw residuals from the multivariate LMM sub-model, respectively |
plot b | the MCEM algorithm convergence trace plots |
sigma | the residual standard errors from the LMM sub-model |
vcov | the variance-covariance matrix of the main parameters of the fitted model (except the baseline hazard) |
getVarCov | the random effects variance-covariance matrix |
confint | the confidence intervals based on asymptotic normality |
update | specific parts of a fitted model can be updated, e.g. by adding or removing terms from a sub-model, and then re-fitted |
sampleData | sample data (with or without replacement) from a joint model |
aprint() also applies to objects of class summary.mjoint and bootSE inheriting from the summary() and bootSE() functions, respectively
bplot() also accepts objects of class ranef.mjoint inheriting from the ranef() function, which displays a caterpillar plot (with 95% prediction intervals) for each random effect
csummary() can also take the optional argument of an object of class bootSE inheriting from the function bootSE(), which overrides the approximate SEs and CIs with those from a bootstrap estimation routine