Calculates predictions and standard errors of predictions for a fitted `repolr`

model object.

1 2 3 |

`object` |
is a model fitted using |

`newdata` |
optionally, a data frame in which to find variables with which to predict; if missing the model fitted values are reported. |

`se.fit` |
Logical indicating if standard errors are required. |

`robust.var` |
logical; if |

`type` |
is the type of prediction required. The default “ |

`...` |
further arguments passed to or from other methods. |

If newdata is missing predictions are based on the data used to fit the `repolr`

model. If newdata are supplied then the format of these data must conform to the same format required for model fitting using `repolr`

. See `repolr`

for details.

`fit` |
Predictions. |

`se.fit` |
Estimated standard errors. |

1 2 3 4 5 6 | ```
data(HHSpain)
mod.0 <- repolr(HHSpain~Sex*Time, data=HHSpain, categories=4, subjects="Patient",
times=c(1,2,5), corr.mod="uniform", alpha=0.5)
predict(mod.0, newdata = data.frame(Patient = rep(100, 3), Time = c(1, 2, 5),
Sex = factor(rep(1, 3), levels=1:2, labels=c("F", "M"))),
type="link", se.fit = TRUE)
``` |

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