In this study, an improved correlational procedure for factor-analyzing dichotomously-scored item response data is described and tested. The procedure involves (a) replacing the dichotomous input values with continuous probability values obtained through Rasch analysis; (b) calculating interitem product-moment correlations among the probabilities; and (c) subjecting the correlations to unweighted least-squares factor analysis. Two simulated data sets and an empirical data set (Kentucky Comprehensive Listening Test responses) were used to compare the new procedure with two more traditional techniques, using (a) phi and (b) tetrachoric correlations calculated directly from the dichotomous item-response values. The three methods were compared on three criterion measures: (a) maximum internal correlation; (b) product of the two largest factor loadings; and (c) proportion of variance accounted for. The Rasch-based procedure is recommended for subjecting dichotomous item response data to latent-variable analysis.

No description available.

This study aimed to better understand visuomotor tracking and spatial visual imagery. 101 Participants performed four tasks: A Manual Tracking Task (MTT), in which participants mouse-tracked the path of a circle, sometimes with occlusion. A Multi-Object Tracking task (MOT), in which participants tracked several objects simultaneously. The Sussex Cognitive Styles Questionnaire (SCSQ), in which participants self-reported their experience with imagery. A Mental Rotation Task (MRT) in which participants mentally rotate Tetris-like objects. The results demonstrated a significant correlation between the technical/spatial subscale of the SCSQ and the occluded MTT, the MRT, the MOT but not the visible MTT. A multiple regression showed that occluded MTT and the MRT together significantly predicted the spatial/technical subscale of the SCSQ above visible MTT and MOT. These findings support the claim that the cognitive resources behind mental imagery may also be recruited during other tasks that arguably draw on the need for internal visualization.

Large, metropolitan areas across the nation have experienced high rates of violent crime over the past 2 decades. As a consequence, law enforcement agencies have increased patrol efforts, but little is known about whether the decrease in violent crime rates was correlated to increased police patrols or to the economic variables of unemployment, inflation, level of education, unemployment compensation, and homeownership. The purpose of this non-experimental, correlational study was to examine the nature of the relationship between increased police patrols, the 5 economic variables, and violent crime rates in 7 large US cities for a 10-year period. The theoretical framework for this study was based on Paternoster's deterrence theory and Becker's economic theory of crime causation. Data were acquired from the Federal Bureau of Investigation and used a sample of 114 cases of reported violent crimes for each city included in the study for the years 2000 - 2010 (n = 798). A multiple regression analysis was initially performed with inconclusive results. Spearman's correlations between each of the independent and dependent variables of violent crime indicated that all the independent variables except for homeownership had statistically significant inverse correlations with violent crime rates. The findings of this study may be used by law enforcement agencies and policy makers to develop crime prevention interventions that address those economic factors associated with violent crime, thereby promoting positive social change through creating safer communities.

<p>The quality of software systems depends on early activities in the software development process, of which the management of requirements is one. When requirements are not managed well, a project can fail or become more costly than intended, and the quality of the software developed can decrease. Among the requirements management practices, it is particularly important to quantify and predict requirements volatility, i.e., how much the requirements are likely to change over time. Software measures can help in quantifying and predicting requirements attributes like volatility. However, few measures have yet been defined, due to the fact that the early phases are hard to formalise. Furthermore, very few requirements measures have been validated, which would be needed in order to demonstrate that they are useful. The approach to requirements management in this thesis is quantitative, i.e. to monitor the requirements management activities and requirements volatility through software measurement. In this thesis, a set of 45 requirements management measures is presented. The measures were defined using the goal question metrics framework for the two predefined goals of the requirements management key process area of the capability maturity model for software. A subset of these measures was validated theoretically and empirically in four case studies. Furthermore, an analysis of validated measures in the literature was performed, showing that there is a lack of validated process, project, and requirements measures in software engineering. The studies presented in this thesis show that size measures are good estimators of requirements volatility. The important result is that size is relevant: increasing the size of a requirements document implies that the number of changes to requirements increases as well. Furthermore, subjective estimations of volatility were found to be inaccurate assessors of requirements volatility. These results suggest that practitioners should complement the subjective estimations for assessing volatility with the objective ones. Requirements engineers and project managers will benefit from the research presented in this thesis because the measures defined, proved to be predictors of volatility, can help in understanding how much requirements will change. By deploying the measures, the practitioners would be prepared for possible changes in the schedule and cost of a project, giving them the possibility of creating alternative plans, new cost estimates, and new software development schedules.</p>

The quality of software systems depends on early activities in the software development process, of which the management of requirements is one. When requirements are not managed well, a project can fail or become more costly than intended, and the quality of the software developed can decrease. Among the requirements management practices, it is particularly important to quantify and predict requirements volatility, i.e., how much the requirements are likely to change over time. Software measures can help in quantifying and predicting requirements attributes like volatility. However, few measures have yet been defined, due to the fact that the early phases are hard to formalise. Furthermore, very few requirements measures have been validated, which would be needed in order to demonstrate that they are useful. The approach to requirements management in this thesis is quantitative, i.e. to monitor the requirements management activities and requirements volatility through software measurement. In this thesis, a set of 45 requirements management measures is presented. The measures were defined using the goal question metrics framework for the two predefined goals of the requirements management key process area of the capability maturity model for software. A subset of these measures was validated theoretically and empirically in four case studies. Furthermore, an analysis of validated measures in the literature was performed, showing that there is a lack of validated process, project, and requirements measures in software engineering. The studies presented in this thesis show that size measures are good estimators of requirements volatility. The important result is that size is relevant: increasing the size of a requirements document implies that the number of changes to requirements increases as well. Furthermore, subjective estimations of volatility were found to be inaccurate assessors of requirements volatility. These results suggest that practitioners should complement the subjective estimations for assessing volatility with the objective ones. Requirements engineers and project managers will benefit from the research presented in this thesis because the measures defined, proved to be predictors of volatility, can help in understanding how much requirements will change. By deploying the measures, the practitioners would be prepared for possible changes in the schedule and cost of a project, giving them the possibility of creating alternative plans, new cost estimates, and new software development schedules.

This study is an investigation of the correlation between Grade 9 students’ self-theories of their intelligence and their tendency for intellectual engagement. Individuals have been shown to self-identify, with respect to their self-theories of intelligence as either entity theorists (who think of their own intelligence as fixed and fairly unchangeable), or incremental theorists (who think of their intelligence as malleable and able to be increased over time). Previous research has shown that individuals have a strong tendency to self-select one or the other of these theoretical frameworks. This study examined the correlation of this identification with individuals’ tendency to become intellectually engaged in their learning. Other demographic factors were also explored. A moderate correlation between students’ self-theory of their intelligence and their tendency for intellectual engagement was demonstrated. In this study, female students showed a higher proportion of an incremental self-theory of intelligence than males. Implications for educational leadership and classroom planning and instruction were explored

Magister Artium (Psychology) - MA(Psych) / Western Cape has the highest prevalence rates of Substance Use Disorder (SUD) with prevalence rates of 18.5%, versus the national average of 13.3%. Existing studies have emphasised that SUD is associated with exposure to trauma and Post-traumatic Stress Disorder (PTSD). In addition, demographic factors such as gender, race and socio-economic status have been correlated with SUD. However, limited research exists on the correlates of SUD among inpatients at substance abuse rehabilitation facilities in the Western Cape Province. The study aimed to address this gap in the literature by investigating the correlates of SUD among inpatients at SUD rehabilitation treatment facilities.

Research suggests youth with disabilities are less likely to experience positive outcomes compared to peers without disabilities. Identification of in-school predictors of postschool success can provide teachers (e.g., special education, general education, career technical education), administrators, district-level personnel, and vocational rehabilitation counselors with information to design, evaluate, and improve transition programs. The purpose of this systematic literature review was to examine secondary transition correlational literature to identify additional evidence to support existing predictors and identify new predictors of postschool success. Results provided additional evidence for 14 existing predictors and identified three new predictors. Limitations and implications for research, policy, and practice are discussed.

One of the most critical issues facing government over the next decade will be filling management positions vacated by Baby Boomers. The purpose of this quantitative correlational research study was to examine how intrinsic and extrinsic motivations affect job satisfaction among different age cohorts in the public workforce. The public workforce is comprised of Baby Boomers (born 1946- 1964), Generation X (born 1965- 1980) and Generation Y (born1981 to 1996). The theoretical framework for this study was Herzberg's motivation-hygiene theory. A random sample of 213 participants: Generation Y = 40, Generation X = 77, and Baby Boomers = 96, participated in an online SurveyMonkey government panel. The panel was composed of local, state, and federal employees. Participants answered the survey using the Career Goals Scale, the Job Satisfaction Scale, and a brief demographics scale. Data were analyzed using descriptive statistics as a measure of central tendency. Also, inferential statistics using Pearson product-moment correlations, simple linear regressions, and one-way multivariate analysis of variance (MANOVA) were conducted to answer three central research questions. Results revealed that both intrinsic and extrinsic motivations affect job satisfaction. Also, results of the individual one-way ANOVAs did not indicate significant differences in intrinsic motivation or job satisfaction among the age cohorts. Finally, pairwise comparisons determined that there were significant differences in extrinsic motivation between Baby Boomers and Generation Y. The information for this study may inform human resource managers in the public sector, about factors that would affect benefit plan policy, and improve recruitment and retention of employees.