The Multidimensional Generalized Graded Unfolding Model (MGGUM) is a proximity-based, noncompensatory item response theory (IRT) model with applications in the context of attitude, personality, and preference measurement. Model development used fully Bayesian Markov Chain Monte Carlo (MCMC) parameter estimation (Roberts, Jun, Thompson, & Shim, 2009a; Roberts & Shim, 2010). Challenges can arise while estimating MGGUM parameters using MCMC where the meaning of dimensions may switch during the estimation process and difficulties in obtaining informative starting values may lead to increased identification of local maxima. Furthermore, researchers must contend with lengthy computer processing time. It has been shown alternative estimation methods perform just as well as, if not better than, MCMC in the unidimensional Generalized Graded Unfolding Model (GGUM; Roberts & Thompson, 2011) with marginal maximum a posteriori (MMAP) item parameter estimation paired with expected a posteriori (EAP) person parameter estimation being a viable alternative. This work implements MMAP/EAP parameter estimation in the multidimensional model. Additionally, item location initial values are derived from detrended correspondence analysis (DCA) based on previous implementation of correspondence analysis in the GGUM (Polak, 2011). A parameter recovery demonstrates the accuracy of two-dimensional MGGUM MMAP/EAP parameter estimates and a comparative analysis of MMAP/EAP and MCMC demonstrates equal accuracy, yet much improved efficiency of the former method. Analysis of real attitude measurement data also provides an illustrative application of the model.

The Functional Limitation Profile (FLP), the Hospital Anxiety and Depression Scale (HADS) and the Recovery Locus of Control scale (RLOC) are three well established and useful measures used in Health Psychology. However, the reliable and valid measurement of these health predictors and outcomes has associated problems. The present thesis tackles measurement issues in all three instruments using item response theory (IRT). The Scientific Advisory Committee of the Medical Outcomes Trust has suggested the methodological and theoretical rationale for the conceptual and measurement model of available measurement instruments should be reported. The introduction chapter provides theoretical background in order to understand activity limitations and participation restrictions as behaviours affected by a certain health condition, as well as by thoughts and feelings. Within this theoretical framework, the present thesis investigates the measurement of mood using the HADS and functional limitations using the FLP in three different health conditions: (1) stroke patients, (2) patients with myocardial infarction, and (3) patients who underwent joint replacement surgery. The measurement of perceived personal control beliefs using the RLOC scale, and the relationship between control cognitions, mood and functional limitations were examined in stroke patients since all three measures were available for secondary analysis in this sample. The main findings are that (1) highly sensitive FLP items measure precisely different levels of disability and handicap, (2) removing 2 HADS items results in precise measurements of different levels of anxiety and depression, and (3) internal but not external perceived personal control beliefs measured sensitively different levels of the underlying construct.

Thesis (Ph. D.)--Georgia State University, 2006. / Karen M. Zabrucky, committee chair; Laura D. Fredrick, John H. Neel, Dennis N. Thompson, committee members. Electronic text (142 p.) : digital, PDF file. Description based on contents viewed July 16, 2007. Includes bibliographical references (p. 129-135).

The effectiveness of multidimensional scaling (MDS) techniques in recovering the underlying dimensionality of dichotomously-scored data was examined for unidimensional and multidimensional data. Thirty-three data sets of varying numbers of dimensions with differing patterns of item discrimination were generated using a multidimensional latent trait model in a Monte Carlo simulation study. Margin-sensitive measures (agreement, phi, and kappa) and margin-free measures (Φ/ Φ(max), Yule's Q, and the tetrachoric correlation) were used as measures of similarity and the resulting matrices were scaled in one through five dimensions. Values of the stress coefficient, S₁, S₁ by dimensionality plots, and plot configurations were examined to determine the dimensionality of the item set. Principal components analyses (PCAs) of phi and tetrachoric matrices were carried out as a basis for comparison. In addition, MDS and PCA were used to examine a data set comprised of items obtained from the routing tests of the Head Start Measures Battery. Two effects of item discrimination on MDS results were especially noteworthy. First, factors tended to be located equally distant from each other in the MDS space. Items were located closest to the factor for which the primary factor loading occurred. Second, as item discrimination decreased, items tended to be more widely dispersed from their appropriate locations in space. Extra dimensions in the MDS representational space were required for margin-sensitive coefficients to accommodate difficulty effects. Margin-free coefficients generally eliminated difficulty-related dimensions, although occasional problems were noted with the tetrachoric correlation. Analysis of the HSMB revealed that the data were primarily unidimensional, although specific effects due to each subtest were clearly present in the analysis. MDS was found to be a useful technique and its use in conjunction with PCA or factor analysis is recommended.

The present study was a systematic investigation of hierarchical skill sequences in the beginning reading domain. The hierarchies included skills from the traditional approach to reading which reflect bottom-up processing and skills from the conceptual area of print awareness which reflect top-down processing. Researchers supporting the bottom-up approach view reading as a process in which the child extracts information from the text to gain knowledge of the print. The bottom-up processes examined were in the areas of letter recognition and letter naming, and identification of letter sounds and phonemes. The top-down processing approach views reading as a task in which the child brings his/her past experiences and knowledge about the world to gain information about print. The top-down processes examined were in the areas of print identification, inferring a word in context, and print directionality rules. Hierarchical skill sequences were developed within each of the specific areas reflecting the top-down and bottom-up processing theories. Items were developed to reflect the skill sequences based on the cognitive processes that are necessary for correct performance. This involved varying the task demands imposing various requirements of cognitive processing. The data were from 13,189 Head Start children ranging from 3 to 6 years of age. Latent trait models were constructed to reflect the viii ix hypothesized skill sequences by allowing the aj (discrimination) and bj (difficulty) parameters to be free to vary or by constraining them to be equal to other parameters. To arrive at a preferred model, each latent trait model that represented a hypothesized skill sequence was statistically compared against alternative latent trait models. The results from the present investigation supported the hierarchical skill sequences reflecting skills within the traditional area of reading. However, some of the skill sequences from the conceptual area of print awareness were not clearly supported. While the results provide a deeper understanding of beginning reading skill sequences reflecting top-down and bottom-up processing theories, future research is needed to delineate the specific skills which promote later reading ability once the child is in formal reading instruction.

Thesis (Ph. D.)--University of Missouri-Columbia, 2008. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on July 28, 2009 Includes bibliographical references.

Personality tests are widely used in the field of Industrial/Organizational Psychology; however, few studies have focused on their psychometric properties using Item Response Theory. This paper uses IRT to examine the test information functions (TIFs) of two personality measures: the NEO-PI-R and scales from the International Personality Item Pool. Results showed that most scales for both measures provided relatively consistent levels of information and measurement precision across levels of theta (q). Although the NEO-PI-R provided overall higher levels of information and measurement precision, the IPIP scales provided greater efficiency in that they provided more precision per item. Both scales showed substantial decrease in precision and information when response scales were dichotomized away from the original 5 point likert scale format. Implications and further avenues for research are discussed. / Master of Science

No description available.

Chi-Keung Leung. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (p. 138-146). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

For equating tests that measure several distinct proficiencies, procedures that reflect the multidimensional structure of the data are needed. Although there exist a few equating procedures developed under the multidimensional item response theory (MIRT) framework, there is a need for further research in this area. Therefore, the primary objectives of this dissertation are to consolidate and expand MIRT observed score equating research with a specific focus on the common-item nonequivalent groups (CINEG) design, which requires scale linking. Content areas and item types are two focal points of dimensionality. This dissertation uses two studies with different data types and comparison criteria to address the research objectives. In general, a comparison between unidimensional item response theory (UIRT) and MIRT methods suggested a better performance of the MIRT methods over UIRT. The simple structure (SS) and full MIRT methods showed more accurate equating results compared to UIRT. In terms of calibration methods, concurrent calibration outperformed separate calibration for all equating methods under most of the studied conditions.