Thesis advisor: Thomas O'Hare / Psychopathy has received a marked increase in attention in the research literature over the past 2 decades since the validation and standardization of assessment tools designed to measure this construct, particularly the Psychopathy Checklist-measures (Hare, 1991/2003; Hart, Cox, & Hare, 1995; and Forth, Kosson, & Hare, 2003). Psychopathy has been identified as the best single predictor of violence among adult offenders (Hart, 1998). Such findings have led some to conclude that "psychopathy is the most important psychological construct for policy and practice in the criminal justice system" (Harris, Skilling, & Rice, 2001). Despite the overwhelming evidence of substantial societal and individual costs attributable to this disorder, little is known about psychosocial precursors of psychopathy. This study examines risk factors related to the development of psychopathy, as measured by the PCL:SV, in a sample of 446 psychiatric patients using structural equation modeling (SEM). The final SEM includes five predictor variables measuring early-life physical abuse, paternal antisocial behavior, and cognitive ability. Severe physical abuse (&beta; = 0.17, <italic>p</italic> = .043), biological father's alcohol abuse history (&beta; = .16, <italic>p</italic> =.004), biological father's arrest history (&beta; = 0.13, <italic>p</italic> = .02), and the subject's cognitive ability (&beta; = -0.18, <italic>p</italic> < .001) were found predictive of psychopathy in this sample. Post hoc analyses comparing male and female subjects, and black and white subjects, indicate different causal pathways in the development of psychopathy among these groups. Future research designed to assess these potentially different causal pathways are recommended. Implications to clinical theory, practice, and policy are also discussed. / Thesis (PhD) — Boston College, 2009. / Submitted to: Boston College. Graduate School of Social Work. / Discipline: Social Work.

Structural equation models are systems of simultaneous linear equations that are generalizations of linear regression, and have many applications in the social, behavioural and biological sciences. A serious barrier to applications is that it is easy to specify models for which the parameter vector is not identifiable from the distribution of the observable data, and it is often difficult to tell whether a model is identified or not. In this thesis, we study the most straightforward method to check for identification – solving a system of simultaneous equations. However, the calculations can easily get very complex. Grobner basis is introduced to simplify the process. The main idea of checking identification is to solve a set of finitely many simultaneous equations, called identifying equations, which can be transformed into polynomials. If a unique solution is found, the model is identified. Grobner basis reduces the polynomials into simpler forms making them easier to solve. Also, it allows us to investigate the model-induced constraints on the covariances, even when the model is not identified. With the explicit solution to the identifying equations, including the constraints on the covariances, we can (1) locate points in the parameter space where the model is not identified, (2) find the maximum likelihood estimators, (3) study the effects of mis-specified models, (4) obtain a set of method of moments estimators, and (5) build customized parametric and distribution free tests, including inference for non-identified models.

Structural equation models are systems of simultaneous linear equations that are generalizations of linear regression, and have many applications in the social, behavioural and biological sciences. A serious barrier to applications is that it is easy to specify models for which the parameter vector is not identifiable from the distribution of the observable data, and it is often difficult to tell whether a model is identified or not. In this thesis, we study the most straightforward method to check for identification – solving a system of simultaneous equations. However, the calculations can easily get very complex. Grobner basis is introduced to simplify the process. The main idea of checking identification is to solve a set of finitely many simultaneous equations, called identifying equations, which can be transformed into polynomials. If a unique solution is found, the model is identified. Grobner basis reduces the polynomials into simpler forms making them easier to solve. Also, it allows us to investigate the model-induced constraints on the covariances, even when the model is not identified. With the explicit solution to the identifying equations, including the constraints on the covariances, we can (1) locate points in the parameter space where the model is not identified, (2) find the maximum likelihood estimators, (3) study the effects of mis-specified models, (4) obtain a set of method of moments estimators, and (5) build customized parametric and distribution free tests, including inference for non-identified models.

Recently, researchers in the organizational behavior have continued their research on the related issues in the perception of organizational politics in the hope to promote organizational trust, and thus achieve the competitive advantages of the organization. Therefore, this study is based on the revised model of the perception of organizational politics, proposed by Ferris et al. (2002), to explore the relation between the perception of organizational politics and organizational trust, and to use SPSS 17.0 and the structural equation model as verification. To re-analyze the research information provided by the research team led by Professor Chin-Ming Ho in the perception of organizational politics, there are discoveries as follows: 1. the dimension of "general political behavior" in the perception of organizational politics has a negative impact to the dimension of "trust manager" in the organizational trust. 2. the dimension of "general political behavior" in the perception of organizational politics has a negative impact to the dimension of "trust organization" in the organizational trust. 3. the dimension of "general political behavior" in the perception of organizational politics has a negative impact to the dimension of "trust colleagues" in the organizational trust. 4. the dimensions of "remain silent, waiting for the benefits" and "difference between policies and practices" in the perception of organizational politics has significantly positive impact to each dimension in the perception of organizational trust.

The number of longitudinal studies has increased steadily in various social science disciplines over the last decade. Growth Mixture Modeling (GMM) has emerged among the new approaches for analyzing longitudinal data. It can be viewed as a combination of Hierarchical Linear Modeling, Latent Growth Curve Modeling and Finite Mixture Modeling. The combination of both continuous and categorical latent variables makes GMM a flexible analysis procedure. However, when researchers analyze their data using GMM, some may assume that the units are independent of each other even though it may not always be the case. The purpose of this dissertation was to examine the impact of ignoring a higher nesting structure in Multilevel Growth Mixture Modeling on the accuracy of classification of individuals and the accuracy on tests of significance (i.e., Type I error rate and statistical power) of the parameter estimates for the model in each subpopulation. Two simulation studies were conducted. In the first study, the impact of misspecifying the multilevel mixture model is investigated by ignoring a level of nesting structure in cross-sectional data. In the second study, longitudinal clustered data (e.g., repeated measures nested within units and units nested within clusters) are analyzed correctly and with a misspecification ignoring the highest level of the nesting structure. Results indicate that ignoring a higher level nesting structure results in lower classification accuracy, less accurate fixed effect estimates, inflation of lower-level variance estimates, and less accurate standard error estimates, the latter result which in turn affects the accuracy of tests of significance for the fixed effects. The magnitude of the intra-class correlation (ICC) coefficient has a substantial impact when a higher level nesting structure is ignored; the higher the ICC, the more variance at the highest level is ignored, and the worse the performance of the model. The implication for applied researchers is that it is important to model the multilevel data structure in (growth) mixture modeling. In addition, researchers should be cautious in interpreting their results if ignoring a higher level nesting structure is inevitable. Limitations concerning appropriate use of latent class analysis in growth modeling include unknown effects of incorrect estimation of the number of latent classes, non-normal distribution effects, and different growth patterns within-group and between-group.

The Improvement Strategy of Kaohsiung Mayor¡¦s Mailbox via Internal Customer Orientation Abstract Under the circumstances of increasing citizen demands and active participation in civil affairs, to improve citizen satisfaction and service quality is the most important things for the government. Actually, whatever the convenient public services or policy vision, these policies products will have great effects on the real life of the public through government employees¡¦ services. In the process of policy output, government employees¡¦ attitude toward the policy will affect the policy performace, and then, leads to citizen satisfation and loyalty. To let the external customer feel satisfied must gratify the internal customer¡¦s desire first. That is to say, to offer good internal service quality to government employees will generate high loyalty to organization, and naturally, the internal customer will give the excellent service quality to external customer. Mayor¡¦s electronic mailbox is the visualization of ¡§the Electronic Government¡¨ or ¡§the Virtual Government¡¨. In addition to providing policy information, governmental service on line, and enhancing citizen participation in public affairs by network technology, it became the vital policy instrument to implement government commitments, and supplied the grievance solving, information sharing, and policy problems construction. This research will discuss the function of customer orientation and it¡¦s effectiveness to inside customer. It began with the present utilization of Mayor¡¦s mailbox, literature review, in-depth interview, questionnaire, and confirm the positive linkage among internal customer orientation, system management mechanism, e-service quality, and internal customer satisfaction. Data were analysed using exploratory and confirmatory factor analysis and structural equation model to test variables and constructs. Finally, this research will put forward a series of proposals, including a short, middle, and long-term improvement strategy for the reference of Kaohsiung city government.

The relationship between budgetary participation, budgetary slack and performance has received a great deal of attention in the literatures of management accounting. However, there is a little consistent conclusion in the relationship between budgetary participation, budgetary slack and performance. Behavior accounting researchers using the Contingent Theory in order to conciliate these inconsistent conclusions also confound contrary results (such as Merchant (1985) and Dunk (1993)). This study suggested that the perceived cause of budgetary participation and the cognitive functions of budgetary participation are important determinants of propensity to create budgetary slack and performance. In addition, this study considered the influence of procedural justice about budgetary decision on budgetary slack and performance. We proposed that there are three actions of participator in the process of participation. The first, subordinate would review the surroundings around themselves like environment uncertainty, task uncertainty, budgetary emphasis, role ambiguity and information asymmetry. The second, subordinates will think the need of functions of participation. The surrounding variables will influence the cognitive functions of participation. Finally, they will decide the subsequent action (in this study we discuss the propensity of budgetary slack and performance). We gathered data from 174 subordinate managers working in the publicly owned companies in Taiwan and used LISREL to test our hypotheses. The results of this study revealed that 1.The cause of budgetary of participation is imperative factor influencing the need of the functions of budgetary participation. The environment uncertainty, task uncertainty, role ambiguity and information asymmetry has positively direct influence on the need of informational effect of budgetary participation respectively. Budgetary emphasis has positively direct influence on the need of affective/motivational effect of budgetary participation. 2.The informational effect of budgetary participation was directive associated with budgetary slack. However, the affective/motivational effect of budgetary participation was indirectly related to budgetary slack through procedural justice. 3. The affective/motivational effect of budgetary participation was directive associated with performance. However, the informational effect of budgetary participation was indirectly related to performance through procedural justice and affective/motivational effect of budgetary participation. We anticipated that the result of this study could offer insight into the relationship between budgetary participation, slack and performance. In addition, we expect to give some suggestions to firms that implement participatory budgeting system to avoid dysfunctional behavior of employees and to encourage performance.

abstract: For this thesis a Monte Carlo simulation was conducted to investigate the robustness of three latent interaction modeling approaches (constrained product indicator, generalized appended product indicator (GAPI), and latent moderated structural equations (LMS)) under high degrees of nonnormality of the exogenous indicators, which have not been investigated in previous literature. Results showed that the constrained product indicator and LMS approaches yielded biased estimates of the interaction effect when the exogenous indicators were highly nonnormal. When the violation of nonnormality was not severe (symmetric with excess kurtosis < 1), the LMS approach with ML estimation yielded the most precise latent interaction effect estimates. The LMS approach with ML estimation also had the highest statistical power among the three approaches, given that the actual Type-I error rates of the Wald and likelihood ratio test of interaction effect were acceptable. In highly nonnormal conditions, only the GAPI approach with ML estimation yielded unbiased latent interaction effect estimates, with an acceptable actual Type-I error rate of both the Wald test and likelihood ratio test of interaction effect. No support for the use of the Satorra-Bentler or Yuan-Bentler ML corrections was found across all three methods. / Dissertation/Thesis / M.A. Psychology 2010

Though the benefits of physical activity are well-studied and accepted, researchers have struggled to identify models of health behavior that accurately predict exercise. This dissertation utilized two components of Bandura's Social-Cognitive Model (self-efficacy and outcome expectancies) and added the construct of fear of failure in order to evaluate what factors influence an individual's decision to exercise or avoid physical activity. Self-report data assessing fear or failure, self-efficacy, outcome expectancies, and physical activity were collected from 248 university students and were analyzed using structural equation modeling techniques in order to evaluate the proposed structural model, which hypothesized that fear of failure would negatively relate to the two Social-Cognitive variables, which were expected to positively predict physical activity engagement. Results revealed that although fear of failure did not add significantly to the Social-Cognitive model, a large portion of the variance in physical activity (i.e., 49%) could be accounted for by the model. Additionally, results indicated that outcome expectancies were a much stronger predictor of physical activity than self-efficacy beliefs. This finding is discussed in relation to how individual differences and genetics may influence how rewarding or aversive individuals find exercising. Implications for intervention and directions for future study, including alternate ways of adding affect to the model are discussed.

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