Assessing the construct validity of a measure of learning agility

This study examined the construct validity of the Choices questionnaire that purported to support the theory of Learning Agility. Specifically, Learning Agility attempts to predict an individual's potential performance in new tasks. The construct validity will be measured by examining the convergent/discriminant validity of the Choices Questionnaire against a cognitive ability measure and two personality measures. The Choices Questionnaire did tap a construct that is unique to the cognitive ability and the personality measures, thus suggesting that this measure may have considerable value in personnel selection. This study also examined the relationship of this pew measure to job performance and job promotability. Results of this study found that the Choices Questionnaire predicted job performance and job promotability above and beyond cognitive ability and personality. Data from 107 law enforcement officers, along with two of their co-workers and a supervisor resulted in a correlation of .08 between Learning Agility and cognitive ability. Learning Agility correlated .07 with Learning Goal Orientation and. 17 with Performance Goal Orientation. Correlations with the Big Five Personality factors ranged from −.06 to. 13 with Conscientiousness and Openness to Experience, respectively. Learning Agility correlated .40 with supervisory ratings of job promotability and correlated .3 7 with supervisory ratings of overall job performance. Hierarchical regression analysis found incremental validity for Learning Agility over cognitive ability and the Big Five factors of personality for supervisory ratings of both promotability and overall job performance. A literature review was completed to integrate the Learning Agility construct into a nomological net of personnel selection research. Additionally, practical applications and future research directions are discussed. ^

Examining a proposed job retention model for adult workers with mental retardation in supported employment

This quantitative study investigated the predictive relationships and interaction between factors such as work-related social behaviors (WRSB), self-determination (SD), person-job congruency (PJC), job performance (JP), job satisfaction (JS), and job retention (JR). A convenience sample of 100 working adults with MR were selected from supported employment agencies. Data were collected using a survey test battery of standardized instruments. The hypotheses were analyzed using three multiple regression analyses to identify significant relationships. Beta weights and hierarchical regression analysis determined the percentage of the predictor variables contribution to the total variance of the criterion variables, JR, JP, and JS. ^ The findings highlight the importance of self-determination skills in predicting job retention, satisfaction, and performance for employees with MR. Consistent with the literature and hypothesized model, there was a predictive relationship between SD, JS and JR. Furthermore, SD and PJC were predictors of JP. SD and JR were predictors of JS. Interestingly, the results indicated no significant relationship between JR and JP, or between JP and JS, or between PJC and JS. This suggests that there is a limited fit between the hypothesized model and the study's findings. However, the theoretical contribution made by this study is that self-determination is a particularly relevant predictor of important work outcomes including JR, JP, and JS. This finding is consistent with Deci's (1992) Self-Determination Theory and Wehmeyer's (1996) argument that SD skills in individuals with disabilities have important consequences for the success in transitioning from school to adult and work life. This study provides job retention strategies that offer rehabilitation and HR professionals a useful structure for understanding and implementing job retention interventions for people with MR. ^ The study concluded that workers with mental retardation who had more self-determination skills were employed longer, more satisfied, and better performers on the job. Also, individuals whose jobs were matched to their interests and abilities (person-job congruency) were better at self-determination skills. ^

Employee engagement: An examination of antecedent and outcome variables

This nonexperimental, correlational study (N = 283) examined the relation among job fit, affective commitment, psychological climate, discretionary effort, intention to turnover, and employee engagement. An internet-based self-report survey battery of six scales were administered to a heterogeneous sampling of organizations from the fields of service, technology, healthcare, retail, banking, nonprofit, and hospitality. Hypotheses were tested through correlational and hierarchical regression analytic procedures. Job fit, affective commitment, and psychological climate were all significantly related to employee engagement and employee engagement was significantly related to both discretionary effort and intention to turnover. For the discretionary effort model, the hierarchical regression analysis results suggested that the employees who reported experiencing a positive psychological climate were more likely to report higher levels of discretionary effort. As for the intention to turnover model, the hierarchical regression analysis results indicated that affective commitment and employee engagement predicted lower levels of an employee’s intention to turnover. The regression beta weights ranged from to .43 to .78, supporting the theoretical, empirical, and practical relevance of understanding the impact of employee engagement on organizational outcomes. Implications for HRD theory, research, and practice are highlighted as possible strategic leverage points for creating conditions that facilitate the development of employee engagement as a means for improving organizational performance.

Fiscal and organizational determinants of transportation outcomes: A quantitative and qualitative analysis of sustainability factors

Federal transportation legislation in effect since 1991 was examined to determine outcomes in two areas: (1) The effect of organizational and fiscal structures on the implementation of multimodal transportation infrastructure, and (2) The effect of multimodal transportation infrastructure on sustainability. Triangulation of methods was employed through qualitative analysis (including key informant interviews, focus groups and case studies), as well as quantitative analysis (including one-sample t-tests, regression analysis and factor analysis). ^ Four hypotheses were directly tested: (1) Regions with consolidated government structures will build more multimodal transportation miles: The results of the qualitative analysis do not lend support while the results of the quantitative findings support this hypothesis, possibly due to differences in the definitions of agencies/jurisdictions between the two methods. (2) Regions in which more locally dedicated or flexed funding is applied to the transportation system will build a greater number of multimodal transportation miles: Both quantitative and qualitative research clearly support this hypothesis. (3) Cooperation and coordination, or, conversely, competition will determine the number of multimodal transportation miles: Participants tended to agree that cooperation, coordination and leadership are imperative to achieving transportation goals and objectives, including targeted multimodal miles, but also stressed the importance of political and financial elements in determining what ultimately will be funded and implemented. (4) The modal outcomes of transportation systems will affect the overall health of a region in terms of sustainability/quality of life indicators: Both the qualitative and the quantitative analyses provide evidence that they do. ^ This study finds that federal legislation has had an effect on the modal outcomes of transportation infrastructure and that there are links between these modal outcomes and the sustainability of a region. It is recommended that agencies further consider consolidation and strengthen cooperation efforts and that fiscal regulations are modified to reflect the problems cited in qualitative analysis. Limitations of this legislation especially include the inability to measure sustainability; several measures are recommended. ^

Risk factors that predict maladaptive outcomes among sexually abused girls presenting for services at a community agency

The purpose of this study was to determine which factors predicted maladaptive outcomes in sexually abused children. Key factors were aggregated into four categories: abuse characteristics risk factors, individual-level risk factors, family disruption risk factors, and social disruption risk factors. It was hypothesized that (a) individual-level risk factors (e.g., school performance, child alcohol/substance abuse) and (b) abuse characteristics risk factors (e.g., longer duration/frequency of abuse, use of force/threats of force, intrafamilial abuse) would predict higher levels of trauma symptoms. Furthermore, it was hypothesized that (a) family disruption risk factors (e.g., family alcohol/substance use, family psychopathology) and (b) social disruption risk factors (e.g., parental divorce, homelessness, witnessing homicide or violence) would moderate the impact of prior sexual abuse and predict higher levels of trauma symptoms. ^ The participants were 110 female children (5 to 18 years old) presenting for treatment for sexual abuse at a community agency (The Journey Institute) in Miami, Florida. This study conducted a retrospective analysis of an archival data set collected over a three-year period (1998–2001). The measures completed upon intake included The Journey Psychosocial Assessment and The Trauma Symptom Checklist for Children (TSCC; Briere, 1996). Using Pearson correlations and hierarchical multiple regression analysis, this study found that abuse characteristics risk factors and individual-level risk factors were predictive of maladaptive outcomes in this sample of sexually abused girls. However, no moderating effects were found for family disruption risk factors or social disruption risk factors. Therefore, the results of these analyses provided support for the contention that abuse characteristics and individual-level risk factors were appropriate targets for treatment for sexually abused girls. Moreover, limitations of this study, implications for treatment, and directions for future research were discussed. ^

Estimation of average annual daily traffic (AADT) using geographically weighted regression (GWR) method and geographic information system (GIS)

Annual average daily traffic (AADT) is important information for many transportation planning, design, operation, and maintenance activities, as well as for the allocation of highway funds. Many studies have attempted AADT estimation using factor approach, regression analysis, time series, and artificial neural networks. However, these methods are unable to account for spatially variable influence of independent variables on the dependent variable even though it is well known that to many transportation problems, including AADT estimation, spatial context is important. ^ In this study, applications of geographically weighted regression (GWR) methods to estimating AADT were investigated. The GWR based methods considered the influence of correlations among the variables over space and the spatially non-stationarity of the variables. A GWR model allows different relationships between the dependent and independent variables to exist at different points in space. In other words, model parameters vary from location to location and the locally linear regression parameters at a point are affected more by observations near that point than observations further away. ^ The study area was Broward County, Florida. Broward County lies on the Atlantic coast between Palm Beach and Miami-Dade counties. In this study, a total of 67 variables were considered as potential AADT predictors, and six variables (lanes, speed, regional accessibility, direct access, density of roadway length, and density of seasonal household) were selected to develop the models. ^ To investigate the predictive powers of various AADT predictors over the space, the statistics including local r-square, local parameter estimates, and local errors were examined and mapped. The local variations in relationships among parameters were investigated, measured, and mapped to assess the usefulness of GWR methods. ^ The results indicated that the GWR models were able to better explain the variation in the data and to predict AADT with smaller errors than the ordinary linear regression models for the same dataset. Additionally, GWR was able to model the spatial non-stationarity in the data, i.e., the spatially varying relationship between AADT and predictors, which cannot be modeled in ordinary linear regression. ^

Emotional intelligence and leadership in organizations: A meta-analytic test of process mechanisms

The present study—employing psychometric meta-analysis of 92 independent studies with sample sizes ranging from 26 to 322 leaders—examined the relationship between EI and leadership effectiveness. Overall, the results supported a linkage between leader EI and effectiveness that was moderate in nature (ρ = .25). In addition, the positive manifold of the effect sizes presented in this study, ranging from .10 to .44, indicate that emotional intelligence has meaningful relations with myriad leadership outcomes including effectiveness, transformational leadership, LMX, follower job satisfaction, and others. Furthermore, this paper examined potential process mechanisms that may account for the EI-leadership effectiveness relationship and showed that both transformational leadership and LMX partially mediate this relationship. However, while the predictive validities of EI were moderate in nature, path analysis and hierarchical regression suggests that EI contributes less than or equal to 1% of explained variance in leadership effectiveness once personality and intelligence are accounted for. ^

Explaining the effects of class size on faculty and students

This study explored the effects of class size on faculty and students. Specifically, it examined the relationship of class size and students' participation in class, faculty interactive styles, and academic environment and how these behaviors affected student achievement (percentage of students passing). The sample was composed of 629 students in 30 sections of Algebra I at a large, urban community college. A survey was administered to the students to solicit their perceptions on their participation in class, their faculty interaction style, and the academic environment in their classes. Selected classes were observed to triangulate the findings. The relationship of class size to student participation, faculty interactive styles, and academic environment was determined by using hierarchical linear modeling (HLM). A significant difference was found on the participation of students related to class size. Students in smaller classes participated more and were more engaged than students in larger classes. Regression analysis using the same variables in small and large classes showed that faculty interactive styles significantly predicted student achievement. Stepwise regression analyses of student and faculty background variables showed that (a) students' estimate of GPA was significantly related to their achievement (r = .63); (b) older students reported more participation than did younger ones, (c) students in classes taught by female, Hispanic faculty earned higher passing grades, and (d) students' participation was greater with adjunct professors. Class observations corroborated these findings. The analysis and observational data provided sufficient evidence to warrant the conclusion that small classes were not always most effective in promoting achievement. It was found that small classes may be an artifact of ineffectual teaching, actual or by reputation. While students in small classes participate and are more engaged than students in larger classes, the class-size effect is essentially due to what happens in instruction to promote learning. The interaction of the faculty with students significantly predicted students' achievement regardless of class size. Since college students select their own classes, students do not register for classes taught by faculty with poor teaching reputation, thereby leading to small classes. Further studies are suggested to determine reasons why classes differ in size.

Development of an instrument to measure high school students' global awareness and attitudes: Looking through the lens of social sciences

The purpose of this study was to develop an instrument to measure high school students’ perspectives on global awareness and attitudes toward social issues. The research questions that guided this study were: (a) Can acceptable validity and reliability estimates be established for an instrument developed to measure high schools students' global awareness? (b) Can acceptable validity and reliability estimates be established for an instrument developed to measure high schools students' attitudes towards global social issues? (c) What is the relationship between high school students’ GPA, race/ethnicity, gender, socio-economic status, parents’ education, getting the news, reading and listening habits, the number of classes taken in the social sciences, whether they speak a second language, and have experienced living in or visiting other countries, and their perception of global awareness and attitudes toward global social issues. ^ An ex post facto research design was used and the data were collected using a 4-part Likert-type survey. It was administered to 14 schools in the Miami-Dade County, Florida area to 704 students. A factor analysis with an orthogonal varimax rotation was vii used to select the factors that best represented the three constructs – global education, global citizenship, and global workforce. This was done to establish construct validity. Cronbach’s alpha was used to determine the reliability of the instrument. Descriptive statistics and a hierarchical multiple regression were used for the demographics to establish their relationship, if any, to the findings. ^ Key findings of the study were that reliable and valid estimates can be developed for the instrument. The multiple regression analysis for model 1 and 2 accounted for a variance of 3% and 5% for self-perceptions of global awareness (factor 1). The regression model also accounted for a 5% and 13% variance in the two models for attitudes toward global social issues (factor 2). The demographics that were statistically significant were: ethnicity, gender, SES, parents’ education, listening to music, getting the news, speaking a second language, GPA, classes taken in the social sciences, and visiting other countries. An important finding for the study was those attending public schools (as opposed to private schools) had more positive attitudes towards global social issues (factor 2) The statistics indicated that these students had taken history, economics, and social studies – a curriculum infused with global perspectives.^

Fiscal decentralization and development: An analysis of city governments in Argentina and Mexico, 1980--2010

This dissertation examines local governments' efforts to promote economic development in Latin America. The research uses a mixed method to explore how cities make decisions to innovate, develop, and finance economic development programs. First, this study provides a comparative analysis of decentralization policies in Argentina and Mexico as a means to gain a better understanding of the degree of autonomy exercised by local governments. Then, it analyzes three local governments each within the province of Santa Fe, Argentina and the State of Guanajuato, Mexico. The principal hypothesis of this dissertation is that if local governments collect more own-source tax revenue, they are more likely to promote economic development and thus, in turn, promote growth for their region. ^ By examining six cities, three of which are in Santa Fe—Rosario, Santa Fe (capital) and Rafaela—and three in Guanajuato—Leon, Guanajuato (capital) and San Miguel de Allende, this dissertation provides a better understanding of public finances and tax collection efforts of local governments in Latin America. Specific attention is paid to each city's budget authority to raise new revenue and efforts to promote economic development. The research also includes a large statistical dataset of Mexico's 2,454 municipalities and a regression analysis that evaluates local tax efforts on economic growth, controlling for population, territorial size, and the professional development. In order to generalize these results, the research tests these discoveries by using statistical data gathered from a survey administered to Latin American municipal officials. ^ The dissertation demonstrates that cities, which experience greater fiscal autonomy measured by the collection of more own-source revenue, are better able to stimulate effective economic development programs, and ultimately, create jobs within their communities. The results are bolstered by a large number of interviews, which were conducted with over 100 finance specialists, municipal presidents, and local authorities. The dissertation also includes an in-depth literature review on fiscal federalism, decentralization, debt financing and local development. It concludes with a discussion of the findings of the study and applications for the practice of public administration.^

Role Stress, Emotional Exhaustion, and Job Satisfaction in the Hotel Industry: The Moderating Role of Supervisory Support

The purpose of this study is to investigate supervisory support as a moderator of the effects of role conflict and role ambiguity on emotional exhaustion and job satisfaction. This study also examines the moderating role of supervisory support on the relationship between emotional exhaustion and job satisfaction. Data were collected from a sample of frontline hotel employees in Northern Cyprus. The aforementioned relationships were tested based on hierarchical multiple regression analysis. The results demonstrate that supervisory support mitigates the impact of role conflict on emotional exhaustion and further reveal that supervisory support reduces the effect of emotional exhaustion on job satisfaction. There is no empirical support for the rest of the hypothesized relationships. Implications of the empirical results are discussed, and future research directions are offered.

The relationship of spirituality and the health promoting behaviors of diet and exercise of African -American women

Public health data show that African-Americans have not adopted health-promoting behaviors of diet and exercise. Spirituality, important in the lives of many African-American women, may be associated with health-promoting behaviors. This study was designed to determine how spirituality relates to health-promoting behaviors in African-American women. Burkhardt's theoretical framework for spirituality was adopted and measures were selected for the three elements of the framework: connectedness with self, others, and environment. ^ The study used a descriptive cross sectional correlational design to investigate the relationships of the independent variables of spirituality, sociodemographics, and BMI, to the dependent variables of diet and exercise, to answer the two primary questions: What is the role of spirituality in impacting the health-promoting behaviors of African-American women? Of the independent variables of spirituality, sociodemographics, and BMI, which are the best predictors of diet and exercise? ^ Central and South Floridian African-American women (n = 260) between 18 and 82 years of age completed several questionnaires: Rosenberg's Self-Esteem Scale, Health Promoting Lifestyle Profile II, Spiritual Perspective Scale, Brief Block Food Frequency, and socio-demographic information. ^ Hierarchical regression identified 40% of the variability of diet to be explained by socio-demographic (education) and spirituality variables (stress management and health responsibility) (p < .001). Twenty-nine percent of the variability of exercise was explained by socio-demographic (education) and spirituality variables (stress management) (p < .001). Canonical correlation analysis identified a significant pair of canonical variates which indicated individuals with good nutrition (.95), increased physical activity (.79), and healthy eating (.42) also had better stress management (.88), better health responsibility (.67), higher spiritual growth (.66), better interpersonal relations (.50), more education (.49), and higher self-esteem (.33). The set explained 57% of the variability (p < .001). ^ An understanding of the factors that influence these women's decision to utilize health-promoting strategies could provide health professionals with additional information to enable them to design culturally and spiritually related health messages for African-American women. The findings of this present study speak of the importance of focusing on stress management, health responsibility, spiritual growth, interpersonal relations and self-esteem along with diet and exercise; this will likely provide improvement in the health-promoting behaviors of African-American women. ^

Predictors of client retention in alternative -to -prison substance abuse programs

Increased treatment retention among substance abusing individuals has been associated with reduced drug use, fewer arrests, and decreased unemployment, as well as a reduction in health risk behaviors. This longitudinal study examined the predictors of client retention for alternative to prison substance abuse treatment programs through assessing the roles of motivational factors and the client-worker relationship. The sample was comprised of 141 male felony offenders who were legally mandated to community based long-term residential drug treatment programs. ^ The primary measures used in the study were the consecutive days a participant remained in treatment, Stages of Change Readiness Model and Treatment Eagerness Scale (SOCRATES), the Working Alliance Inventory (WAI), and The Readiness Ruler. Hierarchical multiple regression analysis was conducted for four hypotheses (a) participants who are more motivated to change at the time of entry will remain in treatment longer, (b) participants who have a strong therapeutic alliance will remain in treatment a greater number of consecutive days than participants who have weaker therapeutic alliance, (c) motivation to change, as measured at treatment entry, will be positively related to therapeutic alliance, (d) during the course of treatment variation in motivation to change will be predicted by the therapeutic alliance. ^ Results support the following conclusions: Among clients in alternative-to prison programs the number of days in treatment is positively related to their motivation to change. The therapeutic alliance is not a predictor of the number of days in treatment. Motivation to change, particularly recognition of a drug problem, is positively related to the therapeutic alliance. Changes in motivation to change in response to treatment are positively related to the therapeutic alliance among clients in an alternative to prison substance abuse treatment programs. These results carry forward prior research and have implications for social work practice, research, and social welfare policy. ^

Employee perceptions of workplace empowerment in relation to self -reported intent to stay on the job

As the nursing profession faces a shortage of nurses, workplace initiatives focused on retaining employees are critical to the United States healthcare industry (Sochalski, 2002). The purpose of this research was to determine whether self-reported intent to stay on the job was related to perceptions of workplace empowerment using Kanter's (1977) theory of organizational empowerment as a framework. ^ The sample consisted of 206 Florida registered nurses. Four self-report scales and a demographic questionnaire were administered by mail. The Conditions for Work Effectiveness Questionnaire (CWEQ; Chandler, 1987), Job Activity Scale (JAS; Laschinger, Kutzscher, & Sabiston, 1993), Organizational Relationships Scale (ORS; Laschinger, Sabiston, & Kutzscher, 1993) and an intent to stay instrument (Kim, Price, Mueller & Watson, 1996) were used to measure perceived access to empowerment structures, perceived formal power, perceived informal power, and intent to stay, respectively. The data were analyzed using descriptive statistics, correlational analysis, and hierarchical regression. ^ Twenty-eight percent of the variance of intent to stay was explained by perceived access to empowerment structures, perceived formal power, and perceived informal power when holding age, gender, education, overall nursing experience, and number of years on current job constant. Perceived access to empowerment structures (CWEQ total score) was the best predictor of self-reported intent to stay for this sample. Of the four components of perceived access to work empowerment structures, perceived access to opportunity and resources were the best predictors of nurses' intent to stay on the job. ^ This study was the first step in establishing the relationship between Kanter's full model and intent to remain on the job, which is a stepping stone for the development of effective retention strategies based on a workplace empowerment model. This knowledge is particularly important in today's healthcare industry where healthcare administrators and human resource development practitioners are ideally positioned to implement organizational strategies to enhance access to work empowerment structures and potentially reduce turnover and mitigate the effects of nursing shortage. ^

Comparison of Some Improved Estimators for Linear Regression Model under Different Conditions

Multiple linear regression model plays a key role in statistical inference and it has extensive applications in business, environmental, physical and social sciences. Multicollinearity has been a considerable problem in multiple regression analysis. When the regressor variables are multicollinear, it becomes difficult to make precise statistical inferences about the regression coefficients. There are some statistical methods that can be used, which are discussed in this thesis are ridge regression, Liu, two parameter biased and LASSO estimators. Firstly, an analytical comparison on the basis of risk was made among ridge, Liu and LASSO estimators under orthonormal regression model. I found that LASSO dominates least squares, ridge and Liu estimators over a significant portion of the parameter space for large dimension. Secondly, a simulation study was conducted to compare performance of ridge, Liu and two parameter biased estimator by their mean squared error criterion. I found that two parameter biased estimator performs better than its corresponding ridge regression estimator. Overall, Liu estimator performs better than both ridge and two parameter biased estimator.