Population-based evidence suggests that the prevalence of psychotic symptoms varies with ethnicity. However, the validity of these self-reported experiences, both as measures of psychotic symptoms per se and as measures of ethnic variation in risk for reporting these symptoms, is questionable. Cultural background and social position may affect the experience and expression of symptoms, which may in turn affect their measurement in survey research. This thesis explores these issues by assessing the psychometric properties of psychosis screening instruments as measures of ethnic differences in psychosis risk in two contexts, Great Britain and the United States. Following this, differences in risk for reporting psychotic symptoms were examined in the context of the varying social and economic conditions to which different ethnic groups and migrant generations are exposed. This was accomplished in the following way: Firstly, the prevalence of self-reported psychotic symptoms was examined across ethnic and generational groups in two large samples of British and American populations; Secondly, the construct validity of the instruments was assessed by means of exploratory and confirmatory factor analyses of response to their symptom indicators. The concurrent validity of the symptoms with measures of self-perceived cognitive and social dysfunction was then examined in a structural equation modeling framework; Thirdly, the cross-ethnic and cross-generational validity of response to these screening instruments was assessed in a multiple-group confirmatory factor analysis framework in which in which the psychometric characteristics of the instruments were compared; And finally, ethnic and generational differences in risk for reporting psychotic symptoms were examined in the context of differential exposure to racial discrimination. Both instruments had construct validity in their measurement of psychotic symptoms, with the exception of one item in the British instrument, as well as concurrent validity with measures of self-perceived cognitive or social dysfunction. The British instrument performed adequately in the measurement of psychotic symptoms across ethnic groups, but did not across migrant generations. The American instrument performed adequately in the measurement of psychotic symptoms across generations, but not across ethnic groups. The effect of measurement noninvariance on the estimation of risk across groups was, however, modest in size. Finally, there was evidence for risk of reporting psychotic symptoms being raised among those who were exposed to racial discrimination. These findings suggest that these self-reported psychotic symptoms constitute clinically relevant phenomena which appear phenotypically similar to the clinical symptoms in diagnosed psychotic disorder. Risk is distributed unevenly over ethnic groups in Britain and the US, is higher among minorities who were exposed to social adversity, and higher among the second generation (in most cases). These patterns are, therefore, highly suggestive of social causation in the aetiology of these self-reported symptoms.

This doctoral thesis ‘Real Estate Development: a Customer Perspective’, mainly concerns questions that are related to why consumers make a choice and what they are looking for. The first part of this thesis is the result of the research project ‘Models for the Construction Sector’ (MoPo) and the second part is the result of a collaborative project between KTH Royal Institute of Technology, the Construction Sector Innovation Centre (BIC), five private companies[1] and four municipalities in Stockholm County. Since the Latham report (Latham, 1994), there has been considerable debate about the need for an increased focus on the end customer in the construction process. The housing sector in Sweden has a strong tradition in focusing on construction and project management issues and less on customer satisfaction. Similar findings have been reported in ‘Skärpning gubbar’ (Swedish Government Official Report, 2002) and recently, ‘Sega gubbar’ (Byggkommisionen, 2009), which show that attitudes and processes in the housing sector in Sweden have not really changed since the initial report in 2002. From the perspective of consumer-oriented research in residential development, this issue concerns the ability to understand why customers buy (cognition), what they want (the product) and how the message, relating the product to the consumer, should be formulated (marketing). Investment decisions could be improved if developers ask what kind of values have proved to be important for residents and buyers for a specific type of residential development, what the functional and psychological consequences they are looking for are, and then ask what kind of product attributes can be provided, given economic constraints. Paper one shows the main activities in how to provide needed facilities and their relationship to the end users’ core business. Paper two shows how the laddering technique can be used to elicit buyers’ beliefs about the built environment, according to the means-end chain theory. The means-end chain theory postulates that buyers purchase a product because it satisfies personal values and desired consequences, which from their perspective are more important than product attributes. Paper three shows the development of a multi-item attitude scale. This scale identifies five key dimensions that are important for the customer when deciding to purchase an apartment in a residential development. The dimensions are: urban environment, architecture, safety, relaxation and liveliness. Paper four shows structural modelling evidence supporting the theoretical assumption that personal values have an impact upon expectations and perceived performance. The structural sub-models show that if perceived performance is increased, customers’ satisfaction will be positively affected. During our research, we have not found any current knowledge in the construction industry in Sweden on how to investigate and measure customers’ values and their beliefs, or how to model customers’ evaluation of product performance using structural equations. [1] Besqab, JM, NCC, Stockholm municipality, Solna municipality, Sollentuna municipality, Swedbank, Upplands-Väsby municipality, Veidekkke. / <p>QC 20100729</p> / Formas 244-2004-183

Companies are increasing their investment in technologies to enable better access to information and to gain a competitive advantage. Global competition is driving companies to reduce costs and enhance productivity, increasing their dependence on information technology. Information is a key asset within an organization and needs to be protected. Expanded connectivity and greater interdependence between companies and consumers has increased the damage potential of a security breach to a company's information systems. Improper unauthorized use of computer systems can create a devastating financial loss even to the point of causing the organization to go out of business. It is critically important to understand what causes users to understand, accept and to follow the organization's information systems security measures so that companies can realize the benefits of their technological investments. In the past several years, computer security breaches have stemmed from insider misuse and abuse of the information systems and non-compliance to the information systems security measures. The purpose of this study was to address the factors that affect employee acceptance of information systems security measures. The Technology Acceptance Model was extended and served as the theoretical framework for this study to examine the factors that affect employee adoption of information systems security measures. The research model included three independent dimensions, perceived ease of use, perceived usefulness and subjective norm. These constructs were hypothesized to predict intention to use information systems security measures, moderated by management support affecting subjective norm. Five hypotheses were posited. A questionnaire was developed to collect data from employees across multiple industry segments to test these hypotheses. Partial least squares statistical methodology was used to analyze the data and to test the hypotheses. The results of the statistical analysis supported three of the five hypotheses with subjective norm and management support showing the strongest effect on intention to use information systems security measures. Few studies have used TAM to study acceptance of systems in a mandatory environment and to specifically examine the employee acceptance of computer information systems security measures. This study, therefore, adds to the body of knowledge. Further, it provides important information for senior management and security professionals across multiple industries regarding the need to develop security policies and processes and to effectively communicate them throughout the organization and to design these measures to promote their use by employees in the organization.

The economy of Taiwan relies heavily upon the electronic manufacturing industry; hence choosing appropriate generic business strategies which are consistent with the environment based on suitable resources can allow small and medium size firms to sustain their competitive advantages and earn a higher return for the electronic manufacturing industry in Taiwan. This study intensities the effect of the precedent factors and generic business strategies chosen on the performance of small and medium size firms in the Taiwanese electronic manufacturing industry. It explores simultaneously the impact of the resources and the environment on business strategy which affects a firm's performance will provide valuable insight into the formulation of competitive strategies by structural equation modeling (SEM) technique. Finally, the use of SAS 9.0 with Amos 5.0 perform first order confirmatory factor analysis for the reliability of questionnaire and explores the relationship among variables in the proposed model based upon path analysis and multiple regression statistical methods and to recommends a new model depending on survey data gathered from firms in Taiwanese electronic manufacturing industry.

The concept of privacy has proven difficult to analyze because of its subjective nature and susceptibility to psychological and contextual influences. This study challenges the concept of privacy as a valid construct for addressing individuals' concerns regarding online disclosure of personal information, based on the premise that underlying behavioral traits offer a more reliable and temporally stable measure of privacy-oriented behavior than do snapshots of environmentally induced emotional states typically measured by opinion polls. This study investigated the relationship of personality characteristics associated with individuals' general privacy-related behavior to their online privacy behaviors and concerns. Two latent constructs, Functional Privacy Orientation and Online Privacy Orientation, were formulated. Functional Privacy Orientation is defined as a general measure of individuals' perception of control over their privacy. It was measured using the factors General Disclosiveness, Locus of Control, Generalized Trust, Risk Orientation, and Risk Propensity as indicator variables. Online Privacy Orientation is defined as a measure of individuals' perception of control over their privacy in an online environment. It was measured using the factors Willingness to Disclose Online, Level of Privacy Concern, Information Management Privacy Concerns, and Reported Online Disclosure as indicator variables. A survey questionnaire that included two new instruments to measure online disclosure and a willingness to disclose online was used to collect data from a sample of 274 adults. Indicator variables for each of the latent constructs, Functional Privacy Orientation and Online Privacy Orientation, were evaluated using corrected item-total correlations, factor analysis, and coefficient alpha. The measurement models and relationship between Functional Privacy Orientation and Online Privacy Orientation were assessed using exploratory factor analysis and structural equation modeling respectively. The structural model supported the hypothesis that Functional Privacy Orientation significantly influences Online Privacy Orientation. Theoretical, methodological, and practical implications and suggestions for analysis of privacy concerns and behavior are presented.

Previous research indicates that stressors experienced by a family, the perceived level of burden assigned by the family to the stressor, and the utilization of resources predict family functioning. The current study utilized a nationally representative sample of families of children with autistic disorder to determine if previously proposed models of family functioning accurately conceptualized family functioning within a representative sample. Structural equation modeling was utilized to test the double ABCX and the linear ACBX models of family functioning. With slight modifications, the double ABCX model was supported, thus indicating that pileup of stressors, perception of burden, and utilization of resources each have unique predictive ability for family functioning, with perception of burden demonstrating the highest amount of predictive ability. Results, implications, and limitations of the study are discussed.

In the current study, I examined the general sociocultural model of eating disorders that suggests that sociocultural pressures leads to internalization, which in turn leads to body dissatisfaction and ultimately disordered eating. Because I am testing this model with a sample of African American women, I also am including acculturation as a variable of interest. Specifically, I hypothesized that (a) the experience of more societal pressure to be thin will be related to greater internalization, (b) higher levels of acculturation will be related to greater internalization, (c) internalization of the thin ideal will be directly and positively related to body image concern, and (d) body image concern will be associated with higher levels of disordered eating. It was determined that there is a direct, negative relationship between Level of Identification with Culture of Origin and Internalization. Perceived Pressure was directly and positively related to both Internalization and Body Image Concerns. Body Concerns and Internalization were both directly and positively related to Disordered Eating. These findings suggest that although many of the same constructs related to disordered eating in other ethnic groups are also related to disordered eating among African American women, the relationships between the factors differs across racial/ethnic groups. This information can help clinicians and researchers to better treat and understand the nature of disordered eating behavior and correlates among African American women.

[pt] O mercado de seguro de automóvel no Brasil apresenta uma concorrência agressiva, indicando que as seguradoras devem investir na fidelização de clientes para buscar sua sobrevivência. Dado isso, este estudo visa testar e analisar hipóteses que abordam a formação da lealdade do cliente no seguro de automóvel com base na análise de efeitos de antecedentes relevantes, como satisfação, custo da mudança, atratividade das alternativas e confiança. A revisão da literatura apresenta e discute modelos de lealdade de acordo com os estudos de Picón et al. (2014) e Aurier e N Goala, (2010). Por meio de uma survey, foi coletada uma amostra de 230 segurados de automóvel. A análise dos dados e o teste das hipóteses propostas foi realizada por meio de modelagem de equações estruturais. Os resultados indicam que satisfação, confiança, atratividade das alternativas e custos de troca impactam diretamente na lealdade do consumidor no mercado de seguro de automóvel. / [en] The car insurance market in Brazil presents aggressive competition, indicating that insurers should invest in customer loyalty to survive. Thus, this study aims to test and analyze hypotheses that address customer loyalty in the insurance market based on the analysis of relevant antecedents of loyalty, such as satisfaction, switching costs, attractiveness of the alternatives and trust. The literature review presents and discusses loyalty models according to Picón et al. (2014) and Aurier and N Goala, (2010). Through a survey, a sample of 230 automobile insurance clients was collected. The proposed model was analyzed via structural equations modeling. The results show that satisfaction, trust, attractiveness of alternatives and switching cost directly affect loyalty in the car insurance industry.

In the educational literature on peer effects, attention has been brought to the fact that the mechanisms creating peer effects are still to a large extent hidden in obscurity. The hypothesis in this study is that the Frame Factor Theory can be used to explain these mechanisms. At heart of the theory is the concept of “time needed” for students to learn a certain curricula unit. The relations between class-aggregated time needed and the actual time available, steers and hinders the actions possible for the teacher. Further, the theory predicts that the timing and pacing of the teachers’ instruction is governed by a “steering criterion group” (SCG), namely the pupils in the 10th-25th percentile of the aptitude distribution in class. The class composition hereby set the possibilities and limitations for instruction, creating peer effects on individual outcomes. To test if the theory can be applied to the issue of peer effects, the study employs multilevel structural equation modelling (M-SEM) on Swedish TIMSS 2015-data (Trends in International Mathematics and Science Study; students N=3761, teachers N=179). Using confirmatory factor analysis (CFA) in the SEM-framework, latent variables are specified according to the theory, such as “limitations of instruction” from TIMSS survey items. The results indicate a good model fit to data of the measurement model. The SEM-model verify a strong relation between the mean level of the SCG and the latent variable of limitations on instruction, a variable which in turn has a great impact on individual students’ test results. Thus, the analysis indicates a confirmation of the predictions derived from the frame factor theory and reveals that one of the important mechanisms creating peer effects in student outcomes is the effect the class composition has upon the teachers’ instruction in class.

<div>Recovering combinatorial structures from noisy observations is a recurrent problem in many application domains, including, but not limited to, natural language processing, computer vision, genetics, health care, and automation. For instance, dependency parsing in natural language processing entails recovering parse trees from sentences which are inherently ambiguous. From a computational standpoint, such problems are typically intractable and call for designing efficient approximation or randomized algorithms with provable guarantees. From a statistical standpoint, algorithms that recover the desired structure using an optimal number of samples are of paramount importance.</div><div><br></div><div>We tackle several such problems in this thesis and obtain computationally and statistically efficient procedures. We demonstrate optimality of our methods by proving fundamental lower bounds on the number of samples needed by any method for recovering the desired structures. Specifically, the thesis makes the following contributions:</div><div><br></div><div>(i) We develop polynomial-time algorithms for learning linear structural equation models --- which are a widely used class of models for performing causal inference --- that recover the correct directed acyclic graph structure under identifiability conditions that are weaker than existing conditions. We also show that the sample complexity of our method is information-theoretically optimal.</div><div><br></div><div>(ii) We develop polynomial-time algorithms for learning the underlying graphical game from observations of the behavior of self-interested agents. The key combinatorial problem here is to recover the Nash equilibria set of the true game from behavioral data. We obtain fundamental lower bounds on the number of samples required for learning games and show that our method is statistically optimal.</div><div><br></div><div>(iii) Lastly, departing from the generative model framework, we consider the problem of structured prediction where the goal is to learn predictors from data that predict complex structured objects directly from a given input. We develop efficient learning algorithms that learn structured predictors by approximating the partition function and obtain generalization guarantees for our method. We demonstrate that randomization can not only improve efficiency but also generalization to unseen data.</div><div><br></div>