# soprobMarkovOrd: soprobMarkovOrd In harrelfe/Hmisc: Harrell Miscellaneous

 soprobMarkovOrd R Documentation

## soprobMarkovOrd

### Description

State Occupancy Probabilities for First-Order Markov Ordinal Model

### Usage

``````soprobMarkovOrd(y, times, initial, absorb = NULL, intercepts, g, ...)
``````

### Arguments

 `y` a vector of possible y values in order (numeric, character, factor) `times` vector of measurement times `initial` initial value of `y` (baseline state; numeric, character, factr) `absorb` vector of absorbing states, a subset of `y`. The default is no absorbing states. (numeric, character, factor) `intercepts` vector of intercepts in the proportional odds model, with length one less than the length of `y` `g` a user-specified function of three or more arguments which in order are `yprev` - the value of `y` at the previous time, the current time `t`, the `gap` between the previous time and the current time, an optional (usually named) covariate vector `X`, and optional arguments such as a regression coefficient value to simulate from. The function needs to allow `yprev` to be a vector and `yprev` must not include any absorbing states. The `g` function returns the linear predictor for the proportional odds model aside from `intercepts`. The returned value must be a matrix with row names taken from `yprev`. If the model is a proportional odds model, the returned value must be one column. If it is a partial proportional odds model, the value must have one column for each distinct value of the response variable Y after the first one, with the levels of Y used as optional column names. So columns correspond to `intercepts`. The different columns are used for `y`-specific contributions to the linear predictor (aside from `intercepts`) for a partial or constrained partial proportional odds model. Parameters for partial proportional odds effects may be included in the ... arguments. `...` additional arguments to pass to `g` such as covariate settings

### Value

matrix with rows corresponding to times and columns corresponding to states, with values equal to exact state occupancy probabilities

Frank Harrell