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A comparison of traditional and IRT ...
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Kay, Cheryl Ann.
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A comparison of traditional and IRT factor analysis.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
A comparison of traditional and IRT factor analysis./
作者:
Kay, Cheryl Ann.
面頁冊數:
108 p.
附註:
Source: Dissertation Abstracts International, Volume: 65-12, Section: A, page: 4538.
Contained By:
Dissertation Abstracts International65-12A.
標題:
Education, Tests and Measurements. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3157486
ISBN:
0496900056
A comparison of traditional and IRT factor analysis.
Kay, Cheryl Ann.
A comparison of traditional and IRT factor analysis.
- 108 p.
Source: Dissertation Abstracts International, Volume: 65-12, Section: A, page: 4538.
Thesis (Ph.D.)--University of North Texas, 2004.
This study investigated the item parameter recovery of two methods of factor analysis. The methods researched were a traditional factor analysis of tetrachoric correlation coefficients and an IRT approach to factor analysis which utilizes marginal maximum likelihood estimation using an EM algorithm (MMLE-EM). Dichotomous item response data was generated under the 2-parameter normal ogive model (2PNOM) using PARDSIM software. Examinee abilities were sampled from both the standard normal and uniform distributions. True item discrimination, a, was normal with a mean of .75 and a standard deviation of .10. True b, item difficulty, was specified as uniform [-2, 2]. The two distributions of abilities were completely crossed with three test lengths (n = 30, 60, and 100) and three sample sizes (N = 50, 500, and 1000). Each of the 18 conditions was replicated 5 times, resulting in 90 datasets. PRELIS software was used to conduct a traditional factor analysis on the tetrachoric correlations. The IRT approach to factor analysis was conducted using BILOG 3 software. Parameter recovery was evaluated in terms of root mean square error, average signed bias, and Pearson correlations between estimated and true item parameters. ANOVAs were conducted to identify systematic differences in error indices. Based on many of the indices, it appears the IRT approach to factor analysis recovers item parameters better than the traditional approach studied. Future research should compare other methods of factor analysis to MMLE-EM under various non-normal distributions of abilities.
ISBN: 0496900056Subjects--Topical Terms:
1017589
Education, Tests and Measurements.
A comparison of traditional and IRT factor analysis.
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This study investigated the item parameter recovery of two methods of factor analysis. The methods researched were a traditional factor analysis of tetrachoric correlation coefficients and an IRT approach to factor analysis which utilizes marginal maximum likelihood estimation using an EM algorithm (MMLE-EM). Dichotomous item response data was generated under the 2-parameter normal ogive model (2PNOM) using PARDSIM software. Examinee abilities were sampled from both the standard normal and uniform distributions. True item discrimination, a, was normal with a mean of .75 and a standard deviation of .10. True b, item difficulty, was specified as uniform [-2, 2]. The two distributions of abilities were completely crossed with three test lengths (n = 30, 60, and 100) and three sample sizes (N = 50, 500, and 1000). Each of the 18 conditions was replicated 5 times, resulting in 90 datasets. PRELIS software was used to conduct a traditional factor analysis on the tetrachoric correlations. The IRT approach to factor analysis was conducted using BILOG 3 software. Parameter recovery was evaluated in terms of root mean square error, average signed bias, and Pearson correlations between estimated and true item parameters. ANOVAs were conducted to identify systematic differences in error indices. Based on many of the indices, it appears the IRT approach to factor analysis recovers item parameters better than the traditional approach studied. Future research should compare other methods of factor analysis to MMLE-EM under various non-normal distributions of abilities.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3157486
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