An investigation on computer-adaptive multistage testing panels for multidimensional assessment

The computer-adaptive multistage testing (ca-MST) has been developed as an alternative to computerized adaptive testing (CAT), and been increasingly adopted in large-scale assessments. Current research and practice only focus on ca-MST panels for credentialing purposes. The ca-MST test mode, therefore, is designed to gauge a single scale. The present study is the first step to investigate ca-MST panels for diagnostic purposes, which involve the assessment of multiple attributes in the same test. This study employed computer simulation to compare multidimensional ca-MST panels and their unidimensional counterparts, and to explore the factors that affect the accuracy and efficiency of multidimensional ca-MST. Nine multidimensional ca-MST panel designs - which differed in configuration and test length - were simulated under varied attribute correlation scenarios. In addition, item pools with different qualities were studied to suggest appropriate item bank design. The comparison between the multidimensional ca-MST and a sequential of unidimensional ca-MST suggested that when attributes correlated moderate to high, employing a multidimensional ca-MST provided more accurate and efficient scoring decisions than several unidimensional ca-MST with IRT scoring. However, a multidimensional ca-MST did not perform better than its unidimensional counterpart with MIRT scoring. Nevertheless, multidimensional panels are still promising for diagnostic purposes given practical considerations. The investigation on multidimensional ca-MST design indicated the following: Higher attribute correlation was associated with better scoring decision because more information carried by a correlation matrix was available for estimation. This held true across all item pool conditions. An optimal item pool would be the one that was discriminative, appropriately located and specifically designed for a configuration. The accuracy and efficiency of a multidimensional ca-MST panel would be diminished if its item pool was too easy, or not informative. According to the results, the 1-2-3 configuration design was most promising. In terms of test length, an appropriate decision would largely depend on the attribute correlation and the item pool characteristics

Effects of herbal products on human P450 2E1 activity

"Cytochromes P450s are present in all forms of life and play an important role in the oxidative transformation of endogeneous and exogeneous molecules. P450 2E1 is a major isoform of cytochrome. The consumption of herbal products in the world is increasing greatly during last decade. The concurrent use of herbal products with prescription carries a risk for unanticipated adverse herb-drug pharmacokinetic interaction, particularly as a result of cytochrome P450 2E1 inhibition. In this research, the preparation and purification of extract of Green Tea, Goldenseal, Echinacea and Spilanthes was performed. In addition, P450 2E1 related activities were to be examined with respect to inhibition by four potential different inhibitors, including GTE, Goldenseal, Echinacea and Spilanthes. The objective of this research is to determine whether herbal products, such as GTE, Goldenseal, Echinacea and Spilanthes, inhibit the activity of the human P450 2E1 enzymes."--Abstract from author supplied metadata

The U.S. plus-size female consumer : self-perception, clothing involvement, and the importance of store attributes

"This study explored how plus-size female consumers perceive their bodies and themselves, how their body-esteem and self-concept may influence involvement with clothing, and how these factors may impact their perceptions of the importance of plus-size store attributes. A preliminary qualitative study of in-depth interviews with four retailers of plus-size apparel and three plus-size consumers was conducted, followed by a quantitative survey study that included sixty female plus-size consumers living in southeastern region of U.S. Results of the hypothesis testing revealed only one significant relationship between plus-size consumers' clothing involvement and perceived importance of store attributes--which was merchandise quality. No significant relationships were found between clothing involvement and the other four store attributes (merchandise price, merchandise assortment, responsiveness of sales personnel, and store display). The results did indicate, however, that consumers' body-esteem and self-concept significantly affect their perceptions of merchandise quality, responsiveness of sales personnel, and store display."--Abstract from author supplied metadata

Knee joint biomechanics after anterior cruciate ligament reconstruction

Anterior cruciate ligament (ACL) is an important stabilizer of the knee joint. After ACL rupture, the knee joint has difficulty maintaining its stability; thus the patient often has to receive an ACL-reconstructive surgery to regain the knee joint functions. Unfortunately, traditional transtibial surgical techniques could not fully restore the normal knee joint kinematics during daily activities. Moreover, a higher rate of osteoarthritis was found from the ACL-reconstructed knees compared to the knees without a history of ACL-injuries. The reason for the increased risk of knee osteoarthritis is still unclear, and the pathologies due to abnormal knee joint kinematics remain controversial. The dissertation was to delineate the knee joint motion and loading after ACL-reconstruction. Thirty patients who received ACL-reconstructive surgeries using the traditional transtibial technique and 14 using the recently developed anteromedial portal technique were recruited from the same center (OrthoCarolina). Twenty healthy subjects without history of knee injuries were recruited as the control group. Human motion data and ground reaction force data were collected during level walking and downstairs pivoting using an optical motion capture system. Three-dimensional (3D) knee joint motions were determined from redundant markers using an optimization approach. The 3D knee joint moments and forces were calculated from motion data, ground reaction data by using an inverse dynamics model of the lower extremity. A finite element model was created, and the distributions of stress/strain within articular cartilage under physiological loading were estimated. The results from two groups of patients using different reconstruction techniques were compared. In the transtibial group, excessive internal tibial rotation (2° on average during stance phase), varus rotation and anterior femur translation (swing phase) were observed in the ACL-reconstructed knees when compared to the control group during level walking. The 3D knee joint motion following ACL-reconstruction was found to be influenced by the leg dominance. The motion and load in the uninjured contralateral knee were also affected. During downstairs pivoting, the normal varus rotation and adduction moment were not fully restored by the transtibial technique. Overall, the anteromedial portal technique improved the postsurgical knee joint kinematics by reducing the offsets in the internal tibial rotation, varus rotation and anterior femur translation during level walking. It also improved the adduction moment during downstairs pivoting. At the same time, the anteromedial portal technique may cause a flexion/extension deficit during the stance phase of walking. Results of finite element analysis demonstrated higher pressures within the medial femoral cartilage during the stance phase of walking; it also demonstrated that there is an increased knee joint laxity after ACL-reconstruction. The anteromedial portal technique was overall better than the traditional transtibial technique in respect to postsurgical knee joint compressive loading and contact pressure. The study provides evidence of the possibility by using anatomical single-bundle ACL-reconstruction technique to fight the knee joint osteoarthritis after ligament injury

Effects of a concept-based physical education curriculum on middle-school students’ out-of-school physical activity

How students’ experience and learning in an educational context influence their self-directed learning and behavior outside of school has always been an important question in education. Scholars have named the effects of physical education (PE) on students’ out-of-school physical activity (PA) as the “PE effect”. The purposes of this dissertation research were to first test a two-pathway model of the “PE effect” and then determine the extent to which a concept-based PE curriculum influenced middle-school students’ PA behavior outside of the school. Specifically, the following research questions were addressed: (a) to what extent did eighth graders’ knowledge and autonomous motivation for PE contribute to their autonomous motivation toward PA and, subsequently, influence their out-of-school PA? (b) Did eighth-grade students who had experienced the Science of Healthful Living (SHL) curriculum have higher levels of knowledge, autonomous motivation for PE, autonomous motivation toward PA, and out-of-school PA than those who had not? A total of 394 eighth-grade students from five schools participated in this study, in which 168 students studied the SHL curriculum when they were in sixth grade while 226 students only experienced traditional PE. Students’ knowledge, out-of-school PA, and autonomous motivation toward PE and PA were measured using valid self-report instruments. Structural equation modelling was used to test the two-pathway model of the “PE effect”. A static group comparison design was adopted to answer the second research question. Results showed that students’ knowledge had a direct, positive relationship on their autonomous motivation toward PA and an indirect, positive relationship on out-of-school PA through influencing autonomous motivation toward PA. Students’ autonomous motivation for PE had a direct, positive relationship on their autonomous motivation toward PA and an indirect, positive relationship on out-of-school PA through autonomous motivation toward PA. The results also showed that the students who had studied the SHL PE curriculum had significantly higher levels of knowledge, autonomous motivation toward PA, and out-of-school PA than the students who had experienced the traditional, multi-activity PE. No significant difference was found for autonomous motivation for PE. These results indicate that the two-pathway model is tenable in terms of knowledge learning and autonomous motivation in PE and imply that teaching knowledge in an autonomy-supportive PE environment can be an effective way to promote students’ out-of-school PA behavior. The findings about the effects of the SHL curriculum further supported the knowledge learning pathway of the “PE effect” and indicate that the concept-based PE approach could be an effective model to promote students’ PA behavior outside of the school

A two-stage framework for designing visual analytics systems to augment organizational analytical processes

A perennially interesting research topic in the field of visual analytics is how to effectively develop systems that support organizational knowledge worker’s decision-making and reasoning processes. The primary objective of a visual analytic system is to facilitate analytical reasoning and discovery of insights through interactive visual interfaces. It also enables the transfer of capability and expertise from where it resides to where it is needed–across individuals, and organizations as necessary. The problem is, however, most domain analytical practices generally vary from organizations to organizations. This leads to the diversified design of visual analytics systems in incorporating domain analytical processes, making it difficult to generalize the success from one domain to another. Exacerbating this problem is the dearth of general models of analytical workflows available to enable such timely and effective designs. To alleviate these problems, this dissertation presents a two-stage framework for informing the design of a visual analytics system. This two-stage design framework builds upon and extends current practices pertaining to analytical workflow and focuses, in particular, on investigating its effect on the design of visual analytics systems for organizational environments. It aims to empower organizations with more systematic and purposeful information analyses through modeling the domain users’ reasoning processes. The first stage in this framework is an Observation and Designing stage, in which a visual analytic system is designed and implemented to abstract and encapsulate general organizational analytical processes, through extensive collaboration with domain users. The second stage is the User-centric Refinement stage, which aims at interactively enriching and refining the already encapsulated domain analysis process based on understanding user’s intentions through analyzing their task behavior. To implement this framework in the process of designing a visual analytics system, this dissertation proposes four general design recommendations that, when followed, empower such systems to bring the users closer to the center of their analytical processes. This dissertation makes three primary contributions: first, it presents a general characterization of the analytical workflow in organizational environments. This characterization fills in the blank of the current lack of such an analytical model and further represents a set of domain analytical tasks that are commonly applicable to various organizations. Secondly, this dissertation describes a two-stage framework for facilitating the domain users’ workflows through integrating their analytical models into interactive visual analytics systems. Finally, this dissertation presents recommendations and suggestions on enriching and refining domain analysis through capturing and analyzing knowledge workers’ analysis processes. To exemplify the generalizability of these design recommendations, this dissertation presents three visual analytics systems that are developed following the proposed recommendations, including Taste for Xerox Corporation, OpsVis for Microsoft, and IRSV for the U.S. Department of Transportation. All of these systems are deployed to domain knowledge workers and are adopted for their analytical practices. Extensive empirical evaluations are further conducted to demonstrate efficacy of these systems in facilitating domain analytical processes

The context of parents and peers: linkages to children's school adjustment

The contexts of family and peer group play critical roles in shaping children's lives over their development. Biological theory suggests that these two contexts are interlinked to impact children's daily lives and should be examined in integrated models. The present study examined relationship quality with peers as a potential mediator that links maternal parenting style to children's school adjustment. Two dimensions of parenting style--maternal responsiveness and behavioral control, and three aspects of school adjustment--academic grades, problem behaviors in the school setting, and school related experiences of stress, were investigated. The mediation models were tested concurrently and longitudinally in a sample of 347 children during their 4th to 5th grades. Biological theory also suggests personal characteristics as one of the defining factors that influence developmental outcomes. Thus, child gender and child ethnicity were included as moderators in the proposed models. Using multiple regressions, results of the study indicated both dimensions of maternal parenting style and peer relationship quality were linked to children's well-being at school concurrently. Surprisingly, peer relationship quality was unassociated with behavioral problems. Short-term longitudinal associations were found between behavioral control and GPA and between responsiveness and school related stress. In terms of mediation, only maternal responsiveness had indirect effects on one of children's outcome variables via its influence on peer relationships concurrently. Also, moderation effects were not found in the proposed mediation models

Three essays on empirical finance

This dissertation includes 3 papers in empirical finance. In chapter 1, since theory suggests a relationship between both volatility of volatility, variance risk premium, and the equity risk premium; we empirically investigate the relationship between volatility of volatility and the equity risk premium, and the relationship between the variance risk premium and the equity risk premium; we find that volatility of volatility alone explains 5 to 10% of the total variation of equity risk premium, and together with VIX data, it explains more than 20% of the total variation of equity premium; and we fail to find a significant relationship between volatility of volatility and the variance risk premium; we also use six measures of volatility of volatility based on non-parametric models, a GARCH model and VVIX data. In chapter 2, we proposes a new way to measure the variance risk premium by applying a fractional cointegration relationship between implied variance and realized variance. To find the fractional cointegration coefficient between implied variance and realized variance, we develop a search method based on minimization of the score test statistic proposed by Robinson(1994). We use daily, weekly and monthly data of five stock market indexes (S&P500, S&P100, DJIA, NASDAQ100 and Russell2000) and their volatility indexes from the CBOE. We find our new measure improves the return prediction power of the variance risk premium both in-sample statically and out-of-sample dynamically, and the result is robust for the monthly data among all five indexes. In chapter 3, by using submortgage data, we found that investors are being charged with a significant risk premium over owner occupants; besides that, they are also facing a more restricted loan; with the market getting hotter, this risk premium and restrictions are getting even worse. Being treated like that, our findings show that investors were actually not more risky than owner occupants in terms of both prepayment and default. We suspect the reason for this puzzle is that when the market getting hotter, there are more speculative investors who commit occupancy fraud to get a more favorable loan. And these speculative investors were actually recorded as owner occupants on loan documents, which increased our estimation of the hazard of owner occupants group. And our information asymmetry test actually reaffirmed our suspect. Therefore, this paper, for the first time, give statistical evidence on occupancy fraud, and we also proposed a statistical scanning way to reduce to potential occupancy fraud

Generalized quasi-likelihood ratio tests for varying coefficient quantile regression models

Quantile regression models which can track the relationship of predictive variables and the response variable in specific quantiles are especially useful in applications when extreme quantiles instead of the center of the distribution are interesting. Compared to classical conditional mean regressions, quantile regression models can provide a more comprehensive structure of the conditional distribution of the response variable. Also, they are more robust to skewed distributions and outliers. Therefore, quantile regression models have been applied extensively in many applied areas. Due to its greater flexibility, a varying coefficient regression technique has been extended to the quantile regression models recently. In this dissertation, my aim is to propose a new test procedure, termed as generalized quasi-likelihood (GQLR) test, to test whether all or partial coefficients are indeed constant or of some specific functions for the varying coefficient quantile regression models. The test statistics are constructed based on the comparison of the quasi-likelihood functions under null and alternative hypotheses. The asymptotic distributions of the proposed test statistics are also derived. First, the functional coefficients in a varying coefficient quantile regression model are estimated by applying local linear fitting technique with jackknife method. Then, I construct the generalized quasi-likelihood ratio test statistics to test whether the varying coefficients are of some specific functional forms, including two special cases: testing whether the varying coefficients are known or unknown constants. The asymptotic normality of the proposed test statistic is derived upon the Bahadur representation of the estimators. I also discuss how to estimate the asymptotic variance-covariance matrix and investigate the power of the proposed test procedures in Chapter 2. Secondly, I consider the similar testing procedure to test if partial coefficients in a varying coefficient quantile regression model are constant or of some specific form with other coefficients completely unspecified in Chapter 3. The corresponding generalized quasi-likelihood ratio test statistic is constructed based on comparing the quasi-likelihood functions under the null and alternative hypotheses. The asymptotic distributions of the proposed test statistics for both constancy and specific functional form are derived respectively and the power of the proposed test procedures is also investigated. Finally, to exam the finite sample performance of all test statistics proposed. In Chapters 2 and 3, Monte Carlo simulation studies are conducted respectively at the end of each chapter. I also apply the proposed test methodologies to test if the existing models in the literature used to analyze the Boston house price data are appropriate or not. The simulation results and the real example illustrate the effectiveness and practical usefulness of the proposed test statistics. Chapter 4 concludes the dissertation. I also discuss some future research topics related to this dissertation

Factor analytic models and cognitive diagnostic models: how comparable are they?--a comparison of R-RUM and compensatory MIRT model with respect to cognitive feedback

The necessity and importance of cognitive diagnosis is being realized by more and more researchers. As a result, a number of models have been defined for cognitive diagnosis--the IRT-based discrete cognitive diagnosis models (ICDMs) and the traditional continuous latent trait models. However, there is a lack of literature that compares the newly defined ICDMs based on constrained latent class models to more traditional approaches such as a multidimensional factor analytic model. The purpose of this study is to compare the feedback provided to examinees using a multidimensional item response model (MIRT) versus feedback provided using an ICDM. Specifically, a Monte Carlo study was used to compare the diagnostic results from the R-RUM, a noncompensatory model with dichotomous abilities, to diagnoses made based on the 2PL CMIRT model, a compensatory model with continuous abilities. A fully crossed design was used to consider the effects of test quality, Q-matrix structure and inter-attribute correlation on the agreement rates of the diagnostic feedback for examinees between these two models. Given that one of the factors of this study is "test quality", an initial study was performed to explore the possible relationship between test quality (including estimated model parameters) based on the models used to characterize examinee responses. In addition, because these models provide examinee information in different ways (one discrete and one continuous), a method using logistic regression, which is used to discretize the continuous estimates provided by the 2PL CMIRT, is discussed as a way to maximize diagnostic agreement between these two models. The significance of this study is that, if the two models agree consistently across the experimental conditions, model selection for cognitive purposes can be based largely on the preference of the researcher, which is informed by an underlying theory and assessment purposes. However, if the two models do not agree consistently, this study will help (1) to identify situations where the two models agree or disagree consistently and (2) to explore the feasibility of using the MIRT model for classifying examinees cognitively