Description Usage Arguments Value References See Also Examples

Estimate a sample selection model in panel counting data, in which the selection equation is a Probit model with random effects on individuals, and the outcome equation is a Poisson Lognormal model with random effects on the same individuals. The random effects on the same individual and the error terms on the same <individual, time> dyad are both correlated across two equations.

1 2 3 4 5 6 | ```
CRE_SS(sel_form, out_form, id, data = NULL, par = NULL, killed_par = NULL,
par_files = NULL, delta = 1, sigma = 1, gamma = 1, max_delta = 3,
max_sigma = 3, max_gamma = 5, rho = 0, tau = 0, lower = c(rho = -1,
tau = -1), upper = c(rho = 1, tau = 1), method = "L-BFGS-B", H = c(10,
10), psnH = 20, prbH = 20, plnreH = 20, accu = 10000,
reltol = sqrt(.Machine$double.eps), verbose = 0, tol_gtHg = Inf)
``` |

`sel_form` |
Formula for selection equation, a probit model with random effects |

`out_form` |
Formula for outcome equation, a Poisson model with random effects |

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

`data` |
Input data, a data frame |

`par` |
Starting values for estimates |

`killed_par` |
correlation parameters to swtich off |

`par_files` |
Loading initial values from saved ProbitRE and PoissonRE estimates |

`delta` |
Variance of random effects on the individual level for ProbitRE |

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

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

`max_delta` |
Largest allowed initial delta |

`max_sigma` |
Largest allowed initial sigma |

`max_gamma` |
Largest allowed initial gamma |

`rho` |
Correlation between random effects on the individual level |

`tau` |
Correlation between error terms on the <individual, time> level |

`lower` |
Lower bound for estiamtes |

`upper` |
Upper bound for estimates |

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

`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 |

`prbH` |
Number of Quddrature points for Probit RE model |

`plnreH` |
Number of Quddrature points for PLN_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`

; `PLN_RE`

;
`PoissonRE`

; `ProbitRE`

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