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<p>Research utilizing the dot probe task to examine attentional bias to threat in social anxiety has yielded inconsistent findings. Many manipulations have been included across dot probe studies, perhaps contributing to the discrepant results. Alternatively, the psychometrics of the dot probe may play a role. Two studies that have examined the psychometric properties of the task found the task to be unreliable (Schmuckle, 2005; Staugaard, 2009).</p> <p>Prompted by the mixed findings, the present study had two overarching goals. The first was to replicate and extend the extant literature by incorporating a number of manipulations into the dot probe task and examining individual differences in social anxiety, and personality types associated with social avoidance and social approach, or shyness and sociability, respectively. The second goal was to investigate the psychometrics of the dot probe task by assessing its test-retest reliability and internal consistency. To address these goals, participants completed a dot probe task that involved manipulations of emotional valence (happy, angry), intensity (moderate, strong), and exposure time (100ms, 500ms) of facial stimuli on two occasions, separated approximately by a month. Additionally, participants were parsed into high and low groups of social anxiety, shyness, and sociability by way of median splits on two personality measures.</p> <p>Using attentional bias scores, a group difference was observed only in the sociability grouping at Time 1. In the low sociability group, a marginal (<em>p</em>=0.049) interaction between valence and intensity was found. This interaction, however, was not observed at Time 2. Additionally, poor test-retest reliability and internal consistency of the task were observed.</p> <p>These findings bring into question the nature of attentional bias in social anxiety, shyness, and sociability, and the psychometric soundness of the dot probe task. Conceptual and psychometric issues are discussed pertaining to the present study’s results and the extant dot probe literature.</p> / Master of Science (MSc)

The personality disorder known as psychopathy describes a group of individuals that have tended to be persistently antisocial and more prone to violence, and demonstrate deficits in affective and interpersonal functioning. Further, the diagnosis of psychopathy (as defined by the PCL-R) reliably predicts recidivism, treatment nonresponse, and other socially important outcomes. Although a well-validated assessment methodology exits for adult correctional populations, more recent research has focused on assessment among adolescents (forensic and nonforensic) and community-based adult populations. The current study examined the psychometric properties of the most promising self-report measures, including their factor structures. Also explored were the unclear relationship between psychopathy and anxiety and related constructs, and the relatively low reliability of scale factors and subscales assessing callousness, a key component of the psychopathy construct, in the research to date. / Psychology

Background: Compared with typically developing children, children with special needs often struggle with academic and social aspects of school, though certain factors can improve their academic and social developmental trajectory. The objective of this investigation was to explore the association between the developmental health of children with special needs at school-entry, as measured by the Early Development Instrument (EDI), and neighborhood-level SES. To date, the EDI has only been validated for use in typically developing children. Hence, a secondary objective of this investigation was to explore the psychometric properties of the EDI for children with special needs. Methods: The data for this investigation were from the Pan-Canadian database of children’s developmental health at school entry. The psychometric properties of the EDI, including item and domain characteristics, factor structure, and construct validity, were tested for children with special needs. Hierarchical generalized linear models was used to model the association between EDI domain scores and a custom neighborhood SES index. Results: A total of 29,841 (69.8% male) and 29,520 (69.7% male) children with special needs were available for the investigation on the psychometric properties of the EDI and the relationship between EDI outcomes and SES, respectively. The psychometric performance of the EDI in children with special needs was similar to its performance in typically developing children. The EDI was subsequently used to explore the association between developmental outcomes and neighborhood socioeconomic status (SES). All EDI domains were positively correlated with SES, indicating that children in high SES neighborhoods have better developmental outcomes at school entry than those in lower SES neighborhoods. Conclusions: The results of this investigation draw attention to the potential impact of contextual factors on children’s health and have implications for policy development and service planning. These results also indicate that the EDI performs similarly in children with special needs and typically developing children, thus enabling its more extensive use for this population. / Thesis / Master of Science (MSc) / Background: Compared with typically developing children, children with special needs often struggle with academic and social aspects of school, though certain factors can improve their academic and social developmental trajectory. The objective of this investigation was to explore the association between the developmental health of children with special needs at school-entry, as measured by the Early Development Instrument (EDI), and neighborhood-level SES. To date, the EDI has only been validated for use in typically developing children. Hence, a secondary objective of this investigation was to explore the psychometric properties of the EDI for children with special needs. Methods: The data for this investigation were from the Pan-Canadian database of children’s developmental health at school entry. The psychometric properties of the EDI, including item and domain characteristics, factor structure, and construct validity, were tested for children with special needs. Hierarchical generalized linear models was used to model the association between EDI domain scores and a custom neighborhood SES index. Results: A total of 29,841 (69.8% male) and 29,520 (69.7% male) children with special needs were available for the investigation on the psychometric properties of the EDI and the relationship between EDI outcomes and SES, respectively. The psychometric performance of the EDI in children with special needs was similar to its performance in typically developing children. The EDI was subsequently used to explore the association between developmental outcomes and neighborhood socioeconomic status (SES). All EDI domains were positively correlated with SES, indicating that children in high SES neighborhoods have better developmental outcomes at school entry than those in lower SES neighborhoods. Conclusions: The results of this investigation draw attention to the potential impact of contextual factors on children’s health and have implications for policy development and service planning. These results also indicate that the EDI performs similarly in children with special needs and typically developing children, thus enabling its more extensive use for this population.

Student misconceptions in science are common and may be present even for students who are academically successful. Concept inventories, multiple-choice tests in which the distractors map onto common, previously identified misconceptions, are commonly used by researchers and educators to gauge the prevalence of student misconceptions in science. Distractor analysis of concept inventory responses could be used to create profiles of individual student misconceptions which could provide deeper insight into the phenomenon and provide useful information for instructional planning, but this is rarely done as the inventories are not designed to facilitate it. Researchers in educational measurement have suggested that diagnostic cognitive models (DCMs) could be used to diagnose misconceptions and to create such misconception profiles. DCMs are multidimensional, confirmatory latent class models which are designed to measure the mastery/presence of fine-grained skills/attributes. By replacing the skills/attributes in the model with common misconceptions, DCMs could be used to filter students into misconception profiles based on their responses to concept inventory-like questions. A few researchers have developed new DCMs that are specifically designed to do this and have retrofitted data from existing concept inventories to them. However, cognitive diagnostic assessments, which are likely to display better model fit with DCMs, have not been developed. This project developed a cognitive diagnostic assessment to measure knowledge and misconceptions about Newton's laws and fitted it with the deterministic input noisy-and-gate (DINA) model. Experienced physics instructors assessed content validity and Q-matrix alignment. A pilot test with 100 undergraduates was conducted to assess item quality within a classical test theory framework. The final version of the assessment was field tested with 349 undergraduates. Results showed that response data displayed acceptable fit to the DINA model at the item level, but more questionable fit at the overall model level; that responses to selected items were similar to those given to two items from the Force Concept Inventory; and that, although all students were likely to have misconceptions, those with lower knowledge scores were more likely to have misconceptions. / Doctor of Philosophy / Misconceptions about science are common even among well-educated adults. Misconceptions range from incorrect facts to personal explanations for natural phenomena that make intuitive sense but are incorrect. Frequently, they exist in people's minds alongside correct science knowledge. Because of this, misconceptions are often difficult to identify and to change. Students may be academically successful and still retain their misconceptions. Concept inventories, multiple-choice tests in which the incorrect answer choices appeal to students with common misconceptions, are frequently used by researchers and educators to gauge the prevalence of student misconceptions in science. Analysis of incorrect answer choices to concept inventory questions can be used to determine individual student's misconceptions, but it is rarely done because the inventories are not known to be valid measures for this purpose. One source of validity for tests is the statistical model that is used to calculate test scores. In valid tests, student's answers to the questions should follow similar patterns to those predicted by the model. For instance, students are likely to get questions about the same things either all correct or all incorrect. Researchers in educational measurement have proposed that certain types of innovative statistical models could be used to develop tests that identify student's misconceptions, but no one has done so. This project developed a test to measure knowledge and misconceptions about forces and assessed how well it predicted student's misconceptions compared to two statistical models. Results showed that the test predicted student's knowledge in good agreement and misconceptions in moderate agreement with the statistical models; that students tended to answer selected questions in the same way that they answered two similar questions from an existing test about forces; and that, although students with lower test scores were more likely to have misconceptions, students with high test scores also had misconceptions.

Although job analysis is basic to almost all human resource functions, little attention has been given to the response format and scoring strategy of job analysis instruments. This study investigated three approaches to scoring polychotomous and dichotomous responses from the frequency and importance scales of the Common Metric Questionnaire (CMQ). Factor, latent trait, and number endorsed scores were estimated from the responses of 2684 job incumbents in six organizations. Scores from four of the CMQ scales were used in linear and nonlinear multiple regression equations to predict pay. The results demonstrated that: (a) simple number endorsed scoring of dichotomous responses was superior to the other scoring strategies; (b) Scoring of dichotomous responses was superior to scoring of polychotomous responses for each scoring technique; (c) scores estimated from the importance scale were better predictors of pay then scores from the frequency scale; (d) the relationship between latent trait and factor scores is nonlinear; (e) latent trait scores estimated with the two-parameter logistic model were superior to latent trait scores from the three parameter model; (f) test information functions for each scale demonstrated that the CMQ scales accurately measured a relatively narrow range of theta; (g) the reliability of factor scores estimated from dichotomous data is superior to factor scores from polychotomous data. Issues regarding the construction of job analysis instruments and the use of item response theory are discussed. / Ph. D.