soprobMarkovOrdm function

soprobMarkovOrdm

State Occupancy Probabilities for First-Order Markov Ordinal Model from a Model Fit

soprobMarkovOrdm(
  object,
  data,
  times,
  ylevels,
  absorb = NULL,
  tvarname = "time",
  pvarname = "yprev",
  gap = NULL
)

Arguments

• object: a fit object created by blrm, lrm, orm, VGAM::vglm(), or VGAM::vgam()
• data: a single observation list or data frame with covariate settings, including the initial state for Y
• times: vector of measurement times
• ylevels: a vector of ordered levels of the outcome variable (numeric or character)
• absorb: vector of absorbing states, a subset of ylevels. The default is no absorbing states. (numeric, character, factor)
• tvarname: name of time variable, defaulting to time
• pvarname: name of previous state variable, defaulting to yprev
• gap: name of time gap variable, defaults assuming that gap time is not in the model

Returns

if object was not a Bayesian model, a matrix with rows corresponding to times and columns corresponding to states, with values equal to exact state occupancy probabilities. If object was created by blrm, the result is a 3-dimensional array with the posterior draws as the first dimension.

Details

Computes state occupancy probabilities for a single setting of baseline covariates. If the model fit was from rms::blrm(), these probabilities are from all the posterior draws of the basic model parameters. Otherwise they are maximum likelihood point estimates.

See Also

https://hbiostat.org/R/Hmisc/markov/

Author(s)

Frank Harrell