The thesis is focused on creating a test battery for the sense of rhythm assessment for university students in the field of Physical Education and sport. Music-sports practice lacks such tests and so far it is forced to use only tests designed for the music field. The structure of the new tests corresponds to the characteristics of the sense of rhythm from the point of view of music psychology. The tests are divided into three sections, which are Perceptual Skills and Activities (items 1 to 18), Reproductive Skills and Activities (items 19 to 27) and Production Skills and Activities (item 28). The Classical test theory (factor analysis) and Item response theory (two-parametric model) were used for the statistical processing of results. The methods also included the calculation of the reliability and validity of the test. The expected refusal of the proposed hypothesis was confirmed in both the classical test theory and item response theory. The exception was model 4, whose fit indexes, especially TLI = 0.537, showed a lack of evidence for the refusal of the hypothesis rather than for a perfect fit of the model with the data. The aim of the research was to compile and test models whose conformity with the data would be the best. The most favorable conformity was for model No. 1 and No. 5. Model 1...

The ability to monitor client change in psychotherapy over time is vital to quality assurance in service delivery as well as the continuing improvement of psychotherapy research. Unfortunately, there is not currently a comprehensive, affordable, and easily utilized outcome measure for psychotherapy specifically normed and standardized for use in psychology training clinics. The current study took the first steps in creating such an outcome measure. Following development of an item bank, factor analysis and item-response theory analyses were applied to data gathered from a stratified sample of university (n = 101) and community (n = 261) participants. The factor structure did not support a phase model conceptualization, but did reveal a structure consistent with the theoretical framework of the research domain criteria (RDoC). Suggestions for next steps in the measure development process are provided and implications discussed.

Context: Medical management for head and neck cancer (HNC) often includes neck dissection surgery, a side effect of which is shoulder dysfunction. There is no consensus for which patient-reported outcome measure (PRO) is most appropriate to quantify shoulder dysfunction in this population. Objective: The aims of this research study were to: (1) use Rasch methodologies to assess construct validity and overall appropriateness of test score interpretation of Disability of the Arm, Shoulder and Hand (DASH), QuickDASH, Shoulder Pain and Disability Index (SPADI) and Neck Dissection Impairment Index (NDII) in the HNC population; (2) determine appropriateness of use of University of Washington Quality of Life (UW-QoL) shoulder subscale as a screening tool for shoulder impairment; (3) recommend a new PRO, or combination of PROs, that more accurately portrays the construct of shoulder dysfunction in the HNC population. Design: One hundred and eight-two individuals who had received a neck dissection procedure within the past 2 weeks to 18 months completed the PROs. Rasch methodologies were utilized to address the primary aim of the study through consideration of scale dimensionality [principal components analysis, item and person fit, differential item functioning (DIF)], scale hierarchy (gaps/redundancies, floor/ceiling effects, coverage of ability levels), response scale structure, and reliability (person and item reliability and separation statistics). The secondary aim was addressed through correlational analysis of the UW-QoL (shoulder subscale), DASH, QuickDASH, SPADI and NDII. Results: The DASH did not meet criteria for unidimensionality, and was deemed inappropriate for utilization in this sample. The QuickDASH, SPADI and NDII were all determined to be unidimensional. All scales had varying issues with person and item misfit, DIF, coverage of ability levels, gaps/redundancies, and optimal rating scale requirements. The NDII meets most requirements. All measures were found to meet thresholds for person and item separation and reliability statistics. The third aim of this study was not addressed because the NDII was determined to be appropriate for this population. Conclusions: Rasch analysis indicates the NDII is the most appropriate measure studied for this population. The QuickDASH and SPADI are recommended with reservation. The DASH and the UW-QoL (shoulder subscale) are not recommended.

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This thesis aims to introduce the use of computerized adaptive testing (CAT) - a novel and ever increasingly used method of a test administration - applied to the field of Kinanthropology. By adapting a test to an individual respondent's latent trait level, computerized adaptive testing offers numerous theoretical and methodological improvements that can significantly advance testing procedures. In the first part of the thesis, the theoretical and conceptual basis of CAT, as well as a brief overview of its historical origins and basic general principles are presented. The discussion necessarily includes the description of Item Response Theory (IRT) to some extent, since IRT is almost exclusively used as the mathematical model in today's CAT applications. Practical application of CAT is then evaluated using Monte-Carlo simulations involving adaptive administration of the Physical Self-Description Questionnaire (PSDQ) (Marsh, Richards, Johnson, Roche, & Tremayne, 1994) - an instrument widely used to assess physical self-concept in the field of sport and exercise psychology. The Monte Carlo simulation of the PSDQ adaptive administration utilized a real item pool (N = 70) calibrated with a Graded Response Model (GRM, see Samejima, 1969, 1997). The responses to test items were generated based on item...

Thesis advisor: Henry I. Braun / Secondary analyses of international large-scale assessments (ILSA) commonly characterize relationships between variables of interest using correlations. However, the accuracy of correlation estimates is impaired by artefacts such as measurement error and clustering. Despite advancements in methodology, conventional correlation estimates or statistical models not addressing this problem are still commonly used when analyzing ILSA data. This dissertation examines the impact of both the clustered nature of the data and heterogeneous measurement error on the correlations reported between background data and proficiency scales across countries participating in ILSA. In this regard, the operating characteristics of competing modeling techniques are explored by means of applications to data from PISA 2012. Specifically, the estimates of correlations between math self-efficacy and math achievement across countries are the principal focus of this study. Sequentially employing four different statistical techniques, a step-wise model refinement approach is used. After each step, the changes in the within-country correlation estimates are examined in relation to (i) the heterogeneity of distributions, (ii) the amount of measurement error, (iii) the degree of clustering, and (iv) country-level math performance. The results show that correlation estimates gathered from two-dimensional IRT models are more similar across countries in comparison to conventional and multilevel linear modeling estimates. The strength of the relationship between math proficiency and math self-efficacy is moderated by country mean math proficiency and this was found to be consistent across all four models even when measurement error and clustering were taken into account. Multilevel multidimensional mixture IRT modeling results support the hypothesis that low-performing groups within countries have a lower correlation between math self-efficacy and math proficiency. A weaker association between math self-efficacy and math proficiency in lower achieving groups is consistently seen across countries. A multilevel mixture IRT modeling approach sheds light on how this pattern emerges from greater randomness in the responses of lower performing groups. The findings from this study demonstrate that advanced modeling techniques not only are more appropriate given the characteristics of the data, but also provide greater insight about the patterns of relationships across countries. / Thesis (PhD) — Boston College, 2021. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement and Evaluation.

Objective: Efficient identification and referral to behavioral services are crucial in addressing early-onset disruptive behavior problems. Existing screening instruments for preschoolers are not ideal for pediatric primary care settings serving diverse populations. Eighteen candidate items for a new brief screening instrument were examined to identify those exhibiting measurement bias (i.e., differential item functioning, DIF) by child characteristics. Method: Parents/guardians of preschool-aged children (N = 900) from four primary care settings completed two full-length behavioral rating scales. Items measuring disruptive behavior problems were tested for DIF by child race, sex, and socioeconomic status using two approaches: item response theory-based likelihood ratio tests and ordinal logistic regression. Results: Of 18 items, eight were identified with statistically significant DIF by at least one method. Conclusions: The bias observed in 8 of 18 items made them undesirable for screening diverse populations of children. These items were excluded from the new brief screening tool.

Guidelines to screen and select common items for vertical scaling have been adopted from equating. Differences between vertical scaling and equating suggest that these guidelines may not apply to vertical scaling in the same way that they apply to equating. For example, in equating the examinee groups are assumed to be randomly equivalent, but in vertical scaling the examinee groups are assumed to possess different levels of proficiency. Equating studies that examined the characteristics of the common-item set stress the importance of careful item selection, particularly when groups differ in ability level. Since in vertical scaling cross-level ability differences are expected, the common items' psychometric characteristics become even more important in order to obtain a correct interpretation of students' academic growth. This dissertation applied two screening criteria and two selection approaches to investigate how changes in the composition of the linking sets impacted the nature of students' growth when creating vertical scales for two elementary mathematics tests. The purpose was to observe how well these equating guidelines were applied in the context of vertical scaling. Two separate datasets were analyzed to observe the impact of manipulating the common items' content area and targeted curricular grade level. The same Rasch scaling method was applied for all variations of the linking set. Both the robust z procedure and a variant of the 0.3-logit difference procedure were used to screen unstable common items from the linking sets. (In vertical scaling, a directional item-difficulty difference must be computed for the 0.3-logit difference procedure.) Different combinations of stable common items were selected to make up the linking sets. The mean/mean method was used to compute the equating constant and linearly transform the students' test scores onto the base scale. A total of 36 vertical scales were created. The results indicated that, although the robust z procedure was a more conservative approach to flagging unstable items, the robust z and the 0.3-logit difference procedure produced similar interpretations of students' growth. The results also suggested that the choice of grade-level-targeted common items affected the estimates of students' grade-to-grade growth, whereas the results regarding the choice of content-area-specific common items were inconsistent. The findings from the Geometry and Measurement dataset indicated that the choice of content-area-specific common items had an impact on the interpretation of students' growth, while the findings from the Algebra and Data Analysis/Probability dataset indicated that the choice of content-area-specific common items did not appear to significantly affect students' growth. A discussion of the limitations of the study and possible future research is presented.

The Missionary Training Center (MTC), affiliated with the Church of Jesus Christ of Latter-day Saints, needs a reliable and cost effective way to measure the oral language proficiency of missionaries learning Spanish. The MTC needed to measure incoming missionaries' Spanish language proficiency for training and classroom assignment as well as to provide exit measures of institutional progress. Oral proficiency interviews and semi-direct assessments require highly trained raters, which is costly and time-consuming. The Elicited Imitation (EI) test is a computerized, automated test that measures oral language proficiency by having the participant hear and repeat utterances of varying syllable length in the target language. It is economical, simple to administer, and rate. This dissertation outlined the process of creating and scoring an EI test for the MTC. Item Response Theory (IRT) was used to analyze a large bank of EI items. The best performing 43 items comprise the final version MTC Spanish EI test. Questions about what linguistic features (syllable length, grammatical difficulty) contribute to item difficulty were addressed. Regression analysis showed that syllable length predicted item difficulty, whereas grammar difficulty did not.