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Semi-Exploratory Factor Analysis and Software to Estimate it
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Name: APSA 2008 Annual Meeting
URL: http://www.apsanet.org
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MLA Citation:

Goodrich, Benjamin. "Semi-Exploratory Factor Analysis and Software to Estimate it" Paper presented at the annual meeting of the APSA 2008 Annual Meeting, Hynes Convention Center, Boston, Massachusetts, Aug 28, 2008 <Not Available>. 2009-05-23 <http://www.allacademic.com/meta/p278355_index.html>

APA Citation:

Goodrich, B. K. , 2008-08-28 "Semi-Exploratory Factor Analysis and Software to Estimate it" Paper presented at the annual meeting of the APSA 2008 Annual Meeting, Hynes Convention Center, Boston, Massachusetts Online <APPLICATION/PDF>. 2009-05-23 from http://www.allacademic.com/meta/p278355_index.html

Publication Type: Conference Paper/Unpublished Manuscript

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Document Type: application/pdf
Page count: 26
Word count: 11819
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Semi-Exploratory Factor Analysis (and Software to Estimate It)∗ Ben Goodrich (goodrich@fas.harvard.edu) and Ryan T. Moore (rtm@wustl.edu) 1 Introduction Factor analysis is a very old statistical method but this paper argues that the way in which factor analysis models are estimated should be fundamentally changed. The new estimator is implemented as an R package and contains two innovations that are particularly noteworthy.1 The first is the ability to impose inequality restrictions on functions of multiple parameters and the second is
The rgenoud package for R.” forthcoming Journal of Statistical Software available from http://sekhon.berkeley.edu/papers/ rgenoudJSS.pdf. Meltzer A.H. & S.F. Richard. 1981. “A Rational Theory of the Size of Government.” The Journal of Political Economy 89(5):914–927. Reiersøl O. 1950. “On the Identification of Parameters in Thurstone’s Multiple Factor Analysis.” Psychometrika 15:121–149. White O. 1966. “Some Properties Of Three Factor Contribution Matrices.” Multivariate Behavioral Research 1(3):373–377. Yates A. 1987. Multivariate Exploratory Data Analysis: A Perspective on Exploratory Factor Analysis. State Uni- versity


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