Description Usage Arguments Value Author(s) Examples

The function computes the conditional probability and information function of each level of each ordinal outcome and the information function at the item level. Confidence bands (and median) can be computed by a Monte Carlo approximation.

1 2 3 4 5 6 7 8 9 |

`x` |
an object inheriting from class |

`lprocess` |
numeric vector containing the latent process values at which the predictions should be computed. |

`condRE_Y` |
for multlcmm objects only, logical indicating if the predictions are conditional to the outcome-specific random-effects or not. Default to FALSE= the predictions are marginal to these random effects. |

`nsim` |
number of points used in the numerical integration (Monte-Carlo) with splines or Beta link functions. nsim should be relatively important (nsim=200 by default). |

`draws` |
optional boolean specifying whether median and confidence bands of the predicted values should be computed (TRUE). A Monte Carlo approximation of the posterior distribution of the predicted values is computed and the median, 2.5% and 97.5% percentiles are given. Otherwise, the predicted values are computed at the point estimate. By default, draws=FALSE. |

`ndraws` |
if draws=TRUE, ndraws specifies the number of draws that should be generated to approximate the posterior distribution of the predicted values. By default, ndraws=2000. |

`...` |
further arguments to be passed to or from other methods. They are ignored in this function. |

An object of class `ItemInfo`

with values :

- `ItemInfo`

:
If draws=FALSE, returns a matrix with 3 columns: the first column indicates the
name of the outcome, the second indicates the latent process value and the last
is the computed Fisher information.
If draws=TRUE, returns a matrix with 5 columns: the name of the outcome, the
latent process value and the 50%, 2.5% and 97.5% percentiles of the approximated
posterior distribution of information.

- `LevelInfo`

:
If draws=FALSE, returns a matrix with 5 columns: the first column indicates the
name of the outcome, the second indicates the outcome's level, the third indicates the
latent process value and the two last contain the probability and Fisher information.
If draws=TRUE, returns a matrix with 5 columns: the name of the outcome,
the outcome's level, the latent process value and the 50%, 2.5% and 97.5%
percentiles of the approximated posterior distribution of the probability and information.

- `object`

: the model from which the computations are done.

- `IC`

: indicator specifying if confidence intervals are computed.

Cecile Proust-Lima, Viviane Philipps

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
## Not run:
## This is a toy example to illustrate the information functions.
## The binary outcomes are arbitrarily created, please do not
## consider them as relevent indicators.
data_lcmm$Yord1 <- as.numeric(data_lcmm$Ydep1>10)
data_lcmm$Yord2 <- as.numeric(data_lcmm$Ydep2>25)
m <- multlcmm(Yord1+Yord2~Time+I(Time^2),random=~Time,subject='ID',ng=1,
data=data_lcmm,link="thresholds")
info <- ItemInfo(m,lprocess=seq(-4,4,length.out=100),draws=TRUE)
plot(info)
par(mfrow=c(1,2))
plot(info, which="LevelInfo", outcome="Yord1")
plot(info, which="LevelInfo", outcome="Yord2")
plot(info, which="LevelProb", outcome="Yord1")
plot(info, which="LevelProb", outcome="Yord2")
## End(Not run)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.