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On Estimating the Mean In Bayesian Factor Analysis

Rowe, Daniel B. (2000) On Estimating the Mean In Bayesian Factor Analysis. Social Science Working Paper, 1096. California Institute of Technology , Pasadena, CA. (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20170808-134717128

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Abstract

In the Bayesian factor analysis model (Press & Shigemasu, 1989), the sample size was assumed to be large enough to estimate the overall population mean by the sample mean. In this paper, the procedure of estimating the population mean by the sample mean is compared to estimating it along with the other parameters both by Gibbs sampling and Iterated Conditional Modes. Results show that even in small samples, the Gibbs sampling and iterated conditional modes estimates of the mean are for practical purposes identical to the sample mean. Thus, the population mean is adequately estimated by its sample value.


Item Type:Report or Paper (Working Paper)
Group:Social Science Working Papers
Series Name:Social Science Working Paper
Issue or Number:1096
Record Number:CaltechAUTHORS:20170808-134717128
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170808-134717128
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:79942
Collection:CaltechAUTHORS
Deposited By: Jacquelyn Bussone
Deposited On:09 Aug 2017 18:55
Last Modified:03 Oct 2019 18:25

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