abstract: Psychological theories often reduce descriptions of people’s emotional experiences to a small number of underlying dimensions that capture most of the variation in their responses. These underlying dimensions are typically uncovered by comparing the self-reported emotions of many individuals at one specific time point, to infer a single underlying structure of emotion for all people. However, theoretical work suggests that underlying dimensions uncovered in this way may not hold when modeling how people change over time. Individuals may differ not just in their typical score on a given dimension of emotion, but in what dimensions best characterize their patterns of emotional experience over time. In this study, participants described two emotional events per day for 35 days, and analyses compared individualized structures of emotion to those generated from many people at one point in time. Analyses using R-technique factor analysis, which compares many people at one time point, most often uncovered a two-factor solution corresponding to positivity and negativity dimensions - a solution well-established in the literature. However, analyses using P-technique factor analysis, which compares many emotional events for one person, uncovered a broader diversity of underlying dimensions. Individuals needed anywhere from one to five factors to best capture their self-reported emotions. Further, dimensions specifically related to romantic relationships were much more common when examining the experiences of individuals over time. This suggests that external factors, such as pursuing or being in a romantic relationship, might lead to a qualitative shift in how emotions are experienced. Research attempting to characterize emotion dynamics, including those attempting to help people shift or regulate their emotions, cannot assume that typical two dimensional structures of emotional experience apply to all people. Instead we must account for how individuals describe their own emotional experiences. / Dissertation/Thesis / Doctoral Dissertation Psychology 2017

Thesis advisor: Thomas O'Hare / The Behavior and Symptom Identification Scale 24 (BASIS-24) is a psychiatric outcome measure used for inpatient and outpatient populations. This 24-item measure comprises six subscales: depression/functioning; interpersonal relationships; self-harm; emotional lability; psychosis; and substance abuse. Earlier studies examined the reliability and validity of the BASIS-24, but none empirically examined its factor structure across gender. The purpose of this study was therefore to assess the construct validity of the BASIS-24 six-factor model and find evidence of configural, metric, strong and strict factorial invariance across gender. The sample consisted of 1398 psychiatric inpatients that completed BASIS-24 at admission and discharge at 11 facilities nation-wide. Confirmatory factor analyses were used to test measurement invariance of the BASIS-24 six-factor model across males and females. The single confirmatory factor analysis showed the original six-factor model of BASIS-24 provided an acceptable fit to the male sample at admission (RMSEA=0.058, SRMR=0.070, CFI=0.975, NNFI=0.971 and GFI=0.977) and at discharge (RMSEA=0.059, SRMR=0 .078, CFI=0.977, NNFI=0.972, and GFI=0.969). The goodness-of-fit indices for the female group at admission (RMSEA=0.055, SRMR=0.067, CFI=0.980, NNFI=0.976, and GFI=0.983), and at discharge (RMSEA=0.055, SRMR=0.079, CFI=0.98, NNFI=0.977, and GFI=0.971) also revealed that the six factor model fit reasonably well to the data. The goodness-of-fit indices between the unconstrained and constrained models showed that all four multi-group models were equivalent for both male and female samples at admission and discharge in terms of goodness-of-fit examined through the &#916;CFI and that all of them show an acceptable fit to the data. The decrease in CFI was <0.008 for admission sample and <0.003 for discharge sample and both fell below the 0.01 cut-off. This indicates that the configural, metric, as well as the strong and strict factorial invariance of BASIS-24 exist across males and females. The two important contributions of the present study are: 1) BASIS-24 can be used as a reliable and valid symptom measurement tool in assessing psychiatric inpatient populations which can compare quantitative differences in the magnitude of patient symptoms and functioning across genders; 2) the current study provides an example of useful statistical methodology for examining specific questions related to factorial invariance of the BASIS-24 instrument across gender. Implications of social work practice and research are discussed. / Thesis (PhD) — Boston College, 2008. / Submitted to: Boston College. Graduate School of Social Work. / Discipline: Social Work.

abstract: The Wechsler Intelligence Scale for Children &ndash; ; Fourth Edition (WISC &ndash; IV) is one of the most popular intelligence tests used for special education eligibility purposes in the United States. Despite the large prevalence of children and adolescents with Attention Deficit Hyperactivity Disorder (ADHD), the factor structure of the WISC &ndash; IV among this population has not been explored. Thus, the factor structure of WISC &ndash; IV scores among students with ADHD was investigated via replicatory factor analysis followed by a comparison with the factorial structure of the normative sample using the coefficient of congruence. The four factor model proposed by Wechsler was consistent with the factor structure found in the sample of students with ADHD for all subtests except Picture Concepts and Matrix Reasoning. The Verbal Comprehension and Processing Speed factors appeared to measure the same construct in the study sample as in the normative sample, while the Perceptual Reasoning and Working Memory factors were only fairly similar to the normative sample. It is recommended that clinicians interpret Perceptual Reasoning and Working Memory index scores of students with ADHD cautiously. Limitations of the study, future directions for research, and implications for practitioners are discussed. / Dissertation/Thesis / M.A. Educational Psychology 2011

This study examined the relationship between self-leadership and personality through an analysis and comparison of hierarchical factor structures. More specifically, this study examined the relationships between the self-leadership dimensions of behavior-focused strategies, natural reward strategies, and constructive thought strategies, and the personality dimensions of extraversion, emotional stability, and conscientiousness. The results of the study provide evidence that the self-leadership dimensions are distinct from, yet related to, the specified personality traits. The hypothesis that self-leadership strategies are distinct from the selected personality traits was supported through structural equations modeling analyses examining competing models combining the hierarchical factor structures of self-leadership and personality. Model fit increased significantly through a progression of models that showed increasingly greater distinction between self-leadership dimensions and personality traits. The best fitting model in the progression, in harmony with both self-leadership and trait personality theory, consisted of a hierarchical factor structure with three first order self-leadership factors, three first order personality factors, and two correlated second order factors (i.e., self-leadership and personality). Furthermore, intercorrelations were greater within the self-leadership dimensions than between the self-leadership dimensions and the personality traits, thus providing additional evidence of differentiation. Although the evidence indicates that self-leadership skill dimensions are unique with respect to personality traits, these results also suggest that self-leadership and personality factors are nevertheless significantly related. Specifically, both extraversion and conscientiousness were significantly related to all three self-leadership dimensions, while emotional stability was significantly related only to the natural rewards strategies dimension. In summation, the results of this study suggest that self-leadership represents a distinct constellation of strategies that are significantly related to certain key personality traits. The implications of these results for future self-leadership research and practice are discussed. / Ph. D.

This dissertation consists of three chapters describing the applications of factor models in different fields of asset pricing. The first chapter addresses the following issue: Prominent volatility-based factor pricing models focus exclusively on the second moment of asset returns, and hence, tend to identify volatile factors but with little risk premia. This chapter demonstrates that a simple asset return transform can arbitrarily upset the ranking of volatility-based factors, but not their prices of risks. Accordingly, we propose a new framework to identify factors based on their prices of risks, or the so-called principally priced risk factors (PPRFs). We construct these factors by generalizing the standard Sharpe ratio for a single asset to a set of assets, incorporating information from both the first and second moments of asset returns. The PPRF framework improves out-of-sample pricing performance in both equity and currency markets. The second chapter identifies the origins of covariance in institutional trading. Conceptually, we introduce two perspectives: the asset perspective, which prioritizes assets as the key market fundamentals, and the manager perspective, which prioritizes fund managers as the key market fundamentals that drive institutional trading covariance. Empirically, we establish that the asset perspective is the primary driver of covariance in institutional trading. Our analysis documents two further empirical patterns. First, returns stemming from the covariance in institutional trading from the asset perspective have higher volatility, offering valuable insights into the demand-based asset pricing literature. Second, the persistence in trading often breaks down during economic downturns, suggesting potential connections to the uncertainty-based business cycle literature. Finally, the third chapter examines the impact of changes in monetary policy rules on the asset valuations of firms with different profitability. I have the following two empirical findings. First, during periods of hawkish monetary policies, the 'profitability premium'— the expected extra return on investments in more profitable firms — tends to increase. Second, when analyzing the factors mediating this effect, changes in inflation expectations play a more significant role in influencing the profitability premium during transitions to a hawkish monetary regime, compared to the effects of real interest rate adjustments on production costs. These observations suggest a possible mechanism by which monetary policy may have different long-term effects on firms with different characteristics. / Doctor of Philosophy / This dissertation explores factor models in asset pricing across three chapters. The first chapter critiques volatility-based models that focus on asset return variance and introduces a new framework for identifying factors based on risk prices, enhancing pricing performance in equity and currency markets. The second chapter investigates the origins of covariance in institutional trading, emphasizing the asset perspective as the dominant influence and documenting higher volatility and breakdowns in trading persistence during economic downturns. The third chapter examines the effects of monetary policy changes on firm asset valuations, finding that hawkish policies increase the profitability premium, significantly influenced by shifts in inflation expectations rather than changes in real interest rates. These insights highlight the nuanced impacts of market fundamentals and monetary policy on asset pricing and firm profitability.

The thesis evaluates the benefit of allowing for long memory volatility dynamics in forecasts of the variance-covariance matrix for asset allocation. First, I compare the forecast performance of multivariate long memory conditional volatility models (the long memory EWMA, long memory EWMA-DCC, FIGARCH-DCC and Component GARCH-DCC models) with that of short memory conditional volatility models (the short memory EWMA and GARCH-DCC models), using the asset allocation framework of Engle and Colacito (2006). The research reports two main findings. First, for longer horizon forecasts, long memory volatility models generally produce forecasts of the covariance matrix that are statistically more accurate and informative, and economically more useful than those produced by short memory volatility models. Second, the two parsimonious long memory EWMA models outperform the other models – both short memory and long memory – in a majority of cases across all forecast horizons. These results apply to both low and high dimensional covariance matrices with both low and high correlation assets, and are robust to the choice of estimation window. The research then evaluates the application of multivariate long memory conditional volatility models in dynamic asset allocation, applying the volatility timing procedure of Fleming et al. (2001). The research consistently identifies the economic gains from incorporating long memory volatility dynamics in investment decisions. Investors are willing to pay to switch from the static to the dynamic strategies, and especially from the short memory volatility timing to the long memory volatility timing strategies across both short and long investment horizons. Among the long memory conditional volatility models, the two parsimonious long memory EWMA models, again, generally produce the most superior portfolios. When transaction costs are taken into account, the gains from the daily rebalanced dynamic portfolios deteriorate; however, it is still worth implementing the dynamic strategies at lower rebalancing frequencies. The results are robust to estimation error in expected returns, the choice of risk aversion coefficients and the use of a long-only constraint. To control for estimation error in forecasts of the long memory high dimensional covariance matrix, the research develops a dynamic long memory factor (the Orthogonal Factor Long Memory, or OFLM) model by embedding the univariate long memory EWMA model of Zumbach (2006) into an orthogonal factor structure. The factor-structured OFLM model is evaluated against the six above multivariate conditional volatility models in terms of forecast performance and economic benefits. The results suggest that the OFLM model generally produces impressive forecasts over both short and long forecast horizons. In the volatility timing framework, portfolios constructed with the OFLM model consistently dominate the static and other dynamic volatility timing portfolios in all rebalancing frequencies. Particularly, the outperformance of the factor-structured OFLM model to the fully estimated LM-EWMA model confirms the advantage of the factor structure in reducing estimation error. The factor structure also significantly reduces transaction costs, making the dynamic strategies more feasible in practice. The dynamic factor long memory volatility model also consistently produces more superior portfolios than those produced by the traditional unconditional factor and the dynamic factor short memory volatility models.

Student-teacher relationships have been studied by numerous researchers from a variety of perspectives. Evidence consistently suggests that the quality of student-teacher relationships can have a profound impact on children’s social and cognitive development. Although researchers seem to agree on this point, their theoretical conceptualizations of the relationships and how they measure them are often quite different. This study provides empirical insights for both measurement integration and theory integration regarding students’ internal relationship representations. Items from 14 different student-teacher relationship instruments were systematically combined and administered as a composite instrument to 628 college students. The participants responded to all items in reference to a single, recent relationship with a high school instructor. This allowed comparative examination of the original 14 scales independently for internal consistency and predictive validity. The study also examined a hypothesized multidimensional structural model of students’ internal representation of their relationship with a teacher based off relational schema theory. An alternative, more parsimonious model was examined as well. The hypothesized model was not supported by the data. The study demonstrated that multiple measurement models of various items could produce acceptable fit. The study provided evidence as to which of the 170 items from the 14 original scales most closely measure the core of student-teacher relationship quality. The study exemplified the method effect dangers of negative item wording. Finally, the study provided strong evidence for conceptualizing student-teacher relationships as a single, global relationship quality construct.

Attention-Deficit Hyperactivity Disorder (ADHD) is one of the most frequent problems for which children are referred to mental health clinics in the United States, affecting approximately 3-5% of the childhood population. Although adequate Ill assessment and identification of this disorder is imperative, most of the currently existing rating scales available to assess for ADHD in the childhood population are inadequate. The present research study involved the investigation of the factor structure and psychometric properties of a new behavior rating scale, the ADHD Symptoms Rating Scale (ADHD-SRS), developed for the assessment of ADHD in the school-age (K-12) population. The participants in this study were 753 children and adolescents (in grades K-12) who were rated by their parents and/or teachers on behavior rating scales designed to measure ADHD characteristics. The results of this research indicate that the ADHD-SRS possesses strong internal consistency. Convergent validity of this instrument was also high. as demonstrated by correlations with two previously validated behavior rating scales. Significant age and gender differences in ADHD symptoms were found with both the parent and teacher respondent populations. The temporal stability of this measure with teacher ratings was low. as was the correlation between parent and teacher ratings of the same children with this instrument. Finally, the factor analysis of the ADHD-SRS suggested a two-factor oblique rotation as the best fit for both the parent and teacher data. After a visual inspection of the items that loaded on each factor, Factor 1 was named Hyperactive-Impulsive and Factor 2 was named Inattention. These two factors, along with the items that loaded on each factor, appear to be remarkably similar to the two categories listed in the DSM-IV for ADHD. Directions for future research. as well as clinical implications and limitations of the current study, are discussed.

The Anorexia Bulimia Inventory, a recently developed self-report questionnaire for the assessment of eating disorders, addresses two major limitations found in existing self-report eating disorder inventories. First, it comprehensively assesses the diagnostic symptoms of both bulimia and anorexia nervosa; and second, it assesses the frequently cooccurring problem areas (e.g., depression, anergia) that may be targeted in treatment planning for eating disorders. Although initial research on the psychometrics of the instrument appears promising, no research has yet investigated its factor structure. Therefore, the goal of the present study was to investigate the factor structure of the Anorexia Bulimia Inventory. Principal axis factor analysis with a varimax rotation was used on a combined clinical and nonclinical sample. The overall sample (N = 1,675) was randomly divided to provide a replication of the factor analysis. Using the two separate samples and the combined, total sample, one seven-factor solution and two eight-factor solutions emerged. All factors met conventional standards for internal consistency, with the exception of one factor consisting of only three items. The results of this study suggest that the factor structure of the Anorexia Bulimia Inventory closely parallels the intuitively designed subscales. All nine subscales emerged as separate, interpretable factors in at least one sample. Four subscales were clearly corroborated by the factor analysis, suggesting that these factors represent stable constructs that are relevant to populations at-risk for the development of eating disorders. The factor analyses provided moderate corroboration of four other subscales. Although these four factors did show deviations across samples, they all emerged as interpretable factors, suggesting that the constructs likely reflect some of the prominent ideational and behavioral issues relevant to at-risk populations. Finally, one subscale emerged as an interpretable factor in only one sample. This failure to replicate across samples may reflect problems in the wording or choice of items included on the subscale, or it could indicate that these issues are less relevant for at-risk populations. The results of this study, together with the existing evidence of the measure's psychometric properties, support the use of the Anorexia Bulimia Inventory in the assessment of eating disorders.

<p>The power of positive attitudes toward science is that they influence science achievement by reinforcing higher performance. Interestingly, there continue to be gender disparities in attitudes toward science across many countries. Males generally have more positive attitudes toward science than females. Although most research related to attitudes toward science have been based on the Trends in International Mathematics and Science Study (TIMSS) Student Questionnaire, there remains a dearth of evidence validating the TIMSS science attitudes items and measurement equivalence across genders. </p><p>The goals of this research were as follows: (1) to build support for the structural validity of the TIMSS items, and (2) to investigate whether the instrument measures the same latent construct (attitudes toward science) across genders. The present study followed two steps of statistical analyses. As a first step, two modeling methods (confirmatory factor analysis and exploratory structural equation modeling) were conducted to identify the best-fitting model for the instrument. Second, after determining the model of choice, we tested several nested invariance models progressively. </p><p>This study found (1) the latent factor structure of the TIMSS items and (2) strong measurement invariance across genders. This result indicated that the instrument is well designed by the <i>a priori</i>specification and measures the same latent variable for both female and male students. This study provides support for the multidimensional approach to measuring science attitudes and shows the flexibility of ESEM over CFA by demonstrating that the ESEM approach provided better representation of the underlying factor structure. </p>