On the Predictive Distributions of Outcome Gains in the Presence of an Unidentified Parameter.

In this paper we describe methods for obtaining the predictive distributions of outcome gains in the framework of a standard latent variable selection model. While most previous work has focused on estimation of mean treatment parameters as the method for characterizing outcome gains from program participation, we show the entire distributions associated with these gains can be accurately obtained on certain situations.

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Year of publication:	2001
Authors:	Poirier, D.J. ; Tobias, J.L.
Institutions:	California Irvine - School of Social Sciences
Subject:	DISTRIBUTION \| OUTCOME \| INFORMATION

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Series:	California Irvine - School of Social Sciences.
Type of publication:	Book / Working Paper
Notes:	37 pages
Classification:	C11 - Bayesian Analysis ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C51 - Model Construction and Estimation
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005641217