Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Magorzata Wojtyś, Giampiero Marra, Rosalba Radice
Title: Copula Regression Spline Sample Selection Models: The R Package SemiParSampleSel
Abstract: Sample selection models deal with the situation in which an outcome of interest is observed for a restricted non-randomly selected sample of the population. The estimation of these models is based on a binary equation, which describes the selection process, and an outcome equation, which is used to examine the substantive question of interest. Classic sample selection models assume a priori that continuous covariates have a linear or pre-specified non-linear relationship to the outcome, and that the distribution linking the two equations is bivariate normal. We introduce the R package SemiParSampleSel which implements copula regression spline sample selection models. The proposed implementation can deal with non-random sample selection, non-linear covariate-response relationships, and non-normal bivariate distributions between the model equations. We provide details of the model and algorithm and describe the implementation in SemiParSampleSel. The package is illustrated using simulated and real data examples.

Page views:: 1882. Submitted: 2013-03-23. Published: 2016-08-01.
Paper: Copula Regression Spline Sample Selection Models: The R Package SemiParSampleSel     Download PDF (Downloads: 1710)
SemiParSampleSel_1.4.tar.gz: R source package Download (Downloads: 142; 71KB)
v71i06.R: R replication code Download (Downloads: 190; 53KB)
ND.dat: Replication data Download (Downloads: 133; 1MB)

DOI: 10.18637/jss.v071.i06

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.