Description Usage Arguments Value Examples

This function predicts probabilities for all choices of a multinomial logit model over a specified span of values.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 |

`model` |
the multinomial model, from a |

`data` |
the data with which the model was estimated |

`x` |
the name of the variable that should be varied (the x-axis variable in prediction plots) |

`by` |
define the steps of |

`z` |
if you want to hold a specific variable stable over all scenarios, you can name it here (optional). |

`z_value` |
determine at which value you want to fix the |

`xvari` |
former argument for |

`scenname` |
former argument for |

`scenvalue` |
former argument for |

`nsim` |
numbers of simulations |

`seed` |
set a seed for replication purposes. |

`probs` |
a vector with two numbers, defining the significance levels. Default to 5% significance level: |

The function returns a list with several elements. Most importantly the list includes the simulated draws 'S', the simulated predictions 'P', and a data set for plotting 'plotdata'.

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
library(nnet)
library(MASS)
dataset <- data.frame(y = c(rep("a", 10), rep("b", 10), rep("c", 10)),
x1 = rnorm(30),
x2 = rnorm(30, mean = 1),
x3 = sample(1:10, 30, replace = TRUE))
mod <- multinom(y ~ x1 + x2 + x3, data = dataset, Hess = TRUE)
pred <- mnl_pred_ova(model = mod, data = dataset,
x = "x1",
nsim = 10)
``` |

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