R: soprobMarkovOrdm

soprobMarkovOrdm {Hmisc} | R Documentation

## soprobMarkovOrdm

### Description

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

### Usage

    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

### 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.

### Value

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.

### Author(s)

Frank Harrell

### See Also

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

[Package Hmisc version 4.7-0 Index]