compare.margins |
Compares two marginal effects (MEMs or AMEs). Estimate of uncertainty is from a simulated draw from a normal distribution. |

count.fit |
Fits four different count models and compares them. |

diagn |
Computes diagnostics for generalized linear models. |

ess |
A subset of data from the European Social Survey |

essUK |
A subset of data from the European Social Survey |

first.diff.fitted |
Computes the first difference in fitted values, or a series of first differences. Inference in supported via the delta method or bootstrapping. |

gss2016 |
Data from the 2016 General Social Survey. |

LF06art |
Data to replicate Long and Freese's (2006) count models (pp354-414) |

LF06travel |
Travel time example data for alternative-specific outcomes. |

list.coef |
Transform glm and mixed model objects into model summaries that include coefficients, standard errors, exponentiated coefficients, confidence intervals and percent change. |

logan |
Replication data for Logan's (1983) application of conditional logistic regression to mobility processes. |

margins.dat |
Add model predictions, standard errors and confidence intervals to a design matrix for a model object. |

margins.dat.clogit |
Computes predicted probabilities for conditional and rank-order/exploded logistic regression models. Inference is based upon simulation techniques (requires the MASS package). Alternatively, bootstrapping is an option for conditional logistic regression models. |

margins.des |
Creates a design matrix of idealized data for illustrating model predictions. |

Mize19AH |
Add-Health Data analzed in Mize (2019) |

Mize19GSS |
General Social Survey Data analzed in Mize (2019) |

rubins.rule |
Aggregate Standard Errors using Rubin's Rule. |

second.diff.fitted |
Computes the second difference in fitted values. Inference in supported via the delta method or bootstrapping. |

wagepan |
Data to illustrate mixed effects regression models with serial correlation. |