Previous research has not shown a clear relationship between order analytic and factor analytic approaches to assessing the dimensionality of binary data. This study compared factor analysis with three order analysis procedures. Comparisons were based on eight datasets with known dimensionality and two multidimensional sets of mathematics data. Two of the order analysis procedures fared poorly in reproducing the factor structure of the datasets. The third procedure reproduced the factors for datasets with orthogonal factors but failed to reproduce the factors for datasets containing oblique factors. Reasons for the differences between these procedures are discussed
This thesis is concerned with two critical issues facing the testing industry today: dimensionality ...
<div><p>This paper undertakes a systematic assessment of the extent to which factor analysis the cor...
We compare the performance of several data permutation methods for assessing dimensionality in Princ...
While factor analysis is the lost ' comaoilly proposed procedure for determining dimensionality...
The isolation of dimensions from a data matrix has been traditionally formulated in terms of an alg...
A monte carlo investigation of three approaches to assessing the dimensionality of binary items use...
This study compared four methods of determining the dimensionality of a set of test items: linear f...
Four methods for determining the dimensionality of a set of test items were compared: (1) linear fac...
Parallel analysis (PA) is an often-recommended approach for assessment of the dimensionality of a va...
184 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1981.Current latent-trait methods ...
Factor Analysis (FA) is a multivariate statistical technique that is often used to create new variab...
The analysis of polychoric correlations via principal component analysis and exploratory factor anal...
<p>Note that the y-axis has different scaling for the factor subspace and the orthogonal complement....
Functional Data Analysis (FDA) deals with samples where a whole function is observedfor each individ...
The effectiveness of multidimensional scaling (MDS) techniques in recovering the underlying dimensio...
This thesis is concerned with two critical issues facing the testing industry today: dimensionality ...
<div><p>This paper undertakes a systematic assessment of the extent to which factor analysis the cor...
We compare the performance of several data permutation methods for assessing dimensionality in Princ...
While factor analysis is the lost ' comaoilly proposed procedure for determining dimensionality...
The isolation of dimensions from a data matrix has been traditionally formulated in terms of an alg...
A monte carlo investigation of three approaches to assessing the dimensionality of binary items use...
This study compared four methods of determining the dimensionality of a set of test items: linear f...
Four methods for determining the dimensionality of a set of test items were compared: (1) linear fac...
Parallel analysis (PA) is an often-recommended approach for assessment of the dimensionality of a va...
184 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1981.Current latent-trait methods ...
Factor Analysis (FA) is a multivariate statistical technique that is often used to create new variab...
The analysis of polychoric correlations via principal component analysis and exploratory factor anal...
<p>Note that the y-axis has different scaling for the factor subspace and the orthogonal complement....
Functional Data Analysis (FDA) deals with samples where a whole function is observedfor each individ...
The effectiveness of multidimensional scaling (MDS) techniques in recovering the underlying dimensio...
This thesis is concerned with two critical issues facing the testing industry today: dimensionality ...
<div><p>This paper undertakes a systematic assessment of the extent to which factor analysis the cor...
We compare the performance of several data permutation methods for assessing dimensionality in Princ...