Formulas of Multilevel Reliabilities for Tests with Ordered Categorical Responses

2021 ◽  
pp. 103-112
Author(s):  
Zhenqiu Lu ◽  
Minju Hong ◽  
Seohyun Kim
Keyword(s):  
Categorical Responses ◽  
Ordered Categorical

scholarly journals The appropriateness of sum scores as estimates of factor scores in the multiple factor analysis of ordered-categorical responses.

2020 ◽  
Author(s):  
Pere Ferrando ◽  
Urbano Lorenzo-Seva
Keyword(s):  
Factor Analysis ◽  
Unit Weight ◽  
Factor Scores ◽  
Multiple Factor Analysis ◽  
Non Linear ◽  
Categorical Responses ◽  
Sum Scores ◽  
Biased Estimates ◽  
Ordered Categorical ◽  
Multiple Factor

<p>Unit-weight sum scores (UWSSs) are routinely used as estimates of factor scores on the basis of solutions obtained with the non-linear exploratory factor analysis (EFA) model for ordered-categorical responses. Theoretically, this practice results in a loss of information and accuracy, and is expected to lead to biased estimates. However, the practical relevance of these limitations is far from clear. In this article we adopt an empirical view, and propose indices and procedures (some of them new) for assessing the appropriateness of UWSSs in non-linear EFA applications. A new automated approach for obtaining UWSSs that maximize fidelity and correlational accuracy is proposed. The appropriateness of UWSSs under different conditions and the behavior of the present proposal in comparison with other more common approaches are assessed with a simulation study. A tutorial for interested practitioners is presented using an illustrative example based on a well-known personality questionnaire. All the procedures proposed in the article have been implemented in a well-known noncommercial EFA program. </p>

scholarly journals The Appropriateness of Sum Scores as Estimates of Factor Scores in the Multiple Factor Analysis of Ordered-Categorical Responses

2020 ◽  
pp. 001316442093810
Author(s):  
Pere J. Ferrando ◽  
Urbano Lorenzo-Seva
Keyword(s):  
Factor Analysis ◽  
Unit Weight ◽  
Practical Relevance ◽  
Factor Scores ◽  
Multiple Factor Analysis ◽  
Categorical Responses ◽  
Sum Scores ◽  
Biased Estimates ◽  
Ordered Categorical ◽  
Multiple Factor

Unit-weight sum scores (UWSSs) are routinely used as estimates of factor scores on the basis of solutions obtained with the nonlinear exploratory factor analysis (EFA) model for ordered-categorical responses. Theoretically, this practice results in a loss of information and accuracy, and is expected to lead to biased estimates. However, the practical relevance of these limitations is far from clear. In this article, we adopt an empirical view and propose indices and procedures (some of them new) for assessing the appropriateness of UWSSs in nonlinear EFA applications. A new automated approach for obtaining UWSSs that maximize fidelity and correlational accuracy is proposed. The appropriateness of UWSSs under different conditions and the behavior of the present proposal in comparison with other more common approaches are assessed with a simulation study. A tutorial for interested practitioners is presented using an illustrative example based on a well-known personality questionnaire. All the procedures proposed in the article have been implemented in a well-known noncommercial EFA program.

Assigning scores for ordered categorical responses

2019 ◽  
Vol 47 (7) ◽  
pp. 1261-1281
Author(s):  
Daniel Fernández ◽  
Ivy Liu ◽  
Roy Costilla ◽  
Peter Yongqi Gu
Keyword(s):  
Categorical Responses ◽  
Ordered Categorical

54 The use of a sample size review in a head injury trial with ordered categorical responses

1997 ◽  
Vol 18 (3) ◽  
pp. S74-S75
Author(s):  
Kim Bolland ◽  
John Whitehead ◽  
M.R. Sooriyarachchi
Keyword(s):  
Head Injury ◽  
Sample Size ◽  
Categorical Responses ◽  
Ordered Categorical

A multidimensional IRT model for continuous and graded responses with error in persons and items

2020 ◽  
Author(s):  
Pere Ferrando ◽  
David Navarro-González
Keyword(s):  
Measurement Precision ◽  
Multidimensional Irt ◽  
Irt Model ◽  
Graded Responses ◽  
Factor Analytic ◽  
Continuous Responses ◽  
Categorical Responses ◽  
Ordered Categorical

This article proposes two multidimensional extensions of existing DMs: the M-DTCRM, intended for (approximately) continuous responses, and the M-DTGRM, intended for ordered-categorical responses (including binary). A rationale for the extension to the multiple-content-dimensions case, which is based on the concept of the multidimensional location index, is first proposed and discussed. Then, the models are described using both the factor-analytic and the IRT parameterizations. Procedures for (a) calibrating the items, (b) scoring individuals, (c) assessing model appropriateness, and (d) assessing measurement precision are finally discussed. The proposals are submitted to be of particular interest for the case of multidimensional questionnaires in which the number of items per scale would not be enough for arriving at stable estimates.

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