soprobMarkovOrdm | R Documentation |

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
)
```

`object` |
a fit object created by |

`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 |

`tvarname` |
name of time variable, defaulting to |

`pvarname` |
name of previous state variable, defaulting to |

`gap` |
name of time gap variable, defaults assuming that gap time is not in the model |

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.

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.

Frank Harrell

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