Description Usage Arguments Value References See Also Examples

Estimate a Poisson Lognormal model with random effects in panel counting data. This model accounts for heterogeneity on the individual level, and heterogeneity on the <individual, time> level.

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`formula` |
Formula of the model |

`id` |
A vector that represents the identity of individuals, numeric or character |

`data` |
Input data, a data frame |

`par` |
Starting values for estimates |

`gamma` |
Variance of random effects on the <individual, time> level for PLN_RE |

`max_gamma` |
Largest allowed initial gamma |

`sigma` |
Variance of random effects on the individual level for PLN_RE |

`max_sigma` |
Largest allowed initial sigma |

`method` |
Searching algorithm, don't change default unless you know what you are doing |

`lower` |
Lower bound for estiamtes |

`upper` |
Upper bound for estimates |

`H` |
A vector of length 2, specifying the number of points for inner and outer Quadratures |

`psnH` |
Number of Quadrature points for Poisson RE model |

`accu` |
L-BFGS-B only, 1e12 for low accuracy; 1e7 for moderate accuracy; 10.0 for extremely high accuracy. See optim |

`reltol` |
Relative convergence tolerance. default typically 1e-8 |

`verbose` |
Level of output during estimation. Lowest is 0. |

`tol_gtHg` |
tolerance on gtHg, not informative for L-BFGS-B |

A list containing the results of the estimated model

1. Jing Peng and Christophe Van den Bulte. Participation vs. Effectiveness of Paid Endorsers in Social Advertising Campaigns: A Field Experiment. Working Paper.

2. Jing Peng and Christophe Van den Bulte. How to Better Target and Incent Paid Endorsers in Social Advertising Campaigns: A Field Experiment. In Proceedings of the 2015 International Conference on Information Systems.

Other PanelCount: `CRE_SS`

; `CRE`

;
`PoissonRE`

; `ProbitRE`

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