The purpose of this study is mainly to discuss the relationship between employer brand, perceived external prestige and word-of-mouth referral. Most of the previous studies about employer brand focus on its recruitment function and also word-of-mouth are mostly applied on the product decision-making. Therefore, this study is seeking to discover the influence of employer brand on triggering employees¡¦ perceived external prestige. By the process of identifying the organization, employees will further have word-of-mouth referral toward public and find the proper potential employees who will be the human capital and further be the competitive advantages for organization. This study uses two questionnaires to collect data from two levels. One of the objects of this study is human resource managers or human resource staffs who have recruitment experiences. Another one is the employee in the firm. There are 34 valid questionnaires of organizational- level and 311 valid questionnaires of individual-level. By adapting the hierarchical linear model to analyze the data and get the result: the employer brand has partially positively influence on word-of-mouth referral, the employer brand has positively influence on the perceived external prestige, the perceived external prestige has positively influence on word-of-mouth referral and the perceived external prestige has partially mediate the positively influence on the relationship between employer brand and word-of-mouth referral.

With data describing 110,520 eighth grade students from 592 junior high (middle) schools in China, a three-level hierarchical linear model was developed in this study to create a multivariate multilevel environment to examine (a) the effects of student-level and school-level variables on science achievement in four subject areas (science inquiry skills, biology, earth science, and physics) and (b) the consistency or stability of academic achievement across the four subject areas among students and among schools. Results indicated that (a) student characteristics, including gender, parental SES, time spent in learning, and the type of family separation, were related to high academic achievement in each of the four science subject areas, (b) no school characteristics were found to be significant factors to affect students’ academic performance in any of the four science subject areas, (c) both students and schools with high academic achievement in one subject area also showed high academic achievement in other subject areas, and (d) the consistency or stability of science performance over the four subject areas did not depend on student characteristics and school characteristics.

abstract: The primary purpose of this study is to examine the effect of knowledge for teaching mathematics and teaching practice on student mathematics achievement growth. Thirty two teachers and 299 fourth grade students in three elementary schools from one school district in urban area participated in the study. Most of them are Hispanic in origin and about forty percent is English Language Learners (ELLs). The two level Hierarchical Linear Model (HLM) was used to investigate repeated measures of teaching practice measured by Classroom Assessment Scoring System (CLASS) instrument. Also, linear regression and a multiple regression to examine the relationship between teacher knowledge measured by Learning for Mathematics Teaching (LMT) and Developing Mathematical Ideas (DMI) items and teaching practice were employed. In addition, a three level HLM was employed to analyze repeated measures of student mathematics achievement measured by Arizona Assessment Consortium (AzAC) instruments. Results showed that overall teaching practice did not change weekly although teachers' emotional support for their students improved by week. Furthermore, a statistically significant relationship between teacher knowledge and teaching practice was not found. In terms of student learning, ELLs have significantly lower initial status in mathematics achievement than non-ELLs, as were growth rates for these two groups. Lastly, teaching practice significantly predicted students' monthly mathematics achievement growth but teacher knowledge did not. The findings suggest that school systems and education policy makers need to provide teachers with the chance to reflect on their teaching and change it within themselves in order to better support student mathematics learning. / Dissertation/Thesis / Ph.D. Curriculum and Instruction 2012

The first semester of practicum is a difficult time for counseling students as they learn to integrate knowledge and theory into clinical practice, often evoking high levels of anxiety (Barbee, Scherer, & Combs, 2003; Ronnestad & Skovholt, 1993) and limiting counselor selfefficacy (Bernard & Goodyear, 2009; Melchert et al., 1996). Practicum is the first opportunity counselors-in-training have to apply theoretical knowledge in a professional setting, use new clinical skills, and test how well they fit into the field of counseling (O‟Connell & Smith, 2005). Additionally, if counselor educators do not fully understand the process counselors in training develop counselor self-efficacy, they may be overlooking opportunities to educate a new generation of counselors or using their time, energy and resources in areas that may not be the most efficient in counselor development. The purpose of this study was to examine the effect of an embedded, rich-media distributed learning environment added to practicum had on the development of counselor self-efficacy, reduction of anxiety and effect on treatment outcomes for counselors in training in their first semester of practicum. This study found the use of distributed learning to extend education beyond the classroom significantly and positively affected the development of counselor selfefficacy, had mixed statistical results on the reduction of anxiety and did not have an affect on treatment outcome. Furthermore, the study used hierarchical linear modeling to see if the characteristics of individual practicums affected the three main constructs, the results did not find a significant effect from the groups. iv The results of the study produced several implications for counseling. First, if counselor educators help counselors in training become more aware of counselor self-efficacy, the students can better understand how the construct affects their anxiety, their comfort with expanding or improving their clinical skills and the approach they take to a client, session or treatment plan. A second implication is that using an embedded, rich-media learning environment may help the counselors in training to develop their clinical skills. The results of this study imply that utilizing technology and discussions beyond the classroom is beneficial for (a) increasing the students‟ counselor self-efficacy, (b) normalizing the emotions the students may experience and (c) improving the methods for development through vicarious learning. Also, as technology continues to evolve and as education continues to adapt by integrating technology into the classrooms, counselor educators should begin exploring how to best use technology to teach students during practicum. Traditionally, based on the nature of counseling, practicum has been an interpersonal experience, but the results of the current study imply the methods of extending learning beyond the traditional class time is beneficial. Finally, as counselor educators strive to increase students‟ counselor self-efficacy early in practicum, in an environment that contains anxiety and self-doubt (Bernard & Goodyear, 2009; Cashwell & Dooley, 2001) using vicarious learning through video and online discussions can assist in accomplishing the goal.

No description available.

Politically interested individual citizens often use information and communication technology (ICT) to facilitate and augment their civic and political participation. At the local level, ICT plays an important role for communication and information sharing in order for local groups to create awareness and draw citizens into public deliberation about local issues and concerns. This research examines the interplay of individual and local group level factors in order to better understand the relationship between civic engagement and ICT, especially the internet, by using household survey data from the town of Blacksburg, Virginia and environs in 2005 and 2006. It seeks to reconcile those different levels of analysis relating to the use and impact of the internet on civic engagement in local governance. This study identifies the distinctive influences at both the individual citizen level and the group level by applying a multilevel statistical model (the Hierarchical Linear Model). First, this study found the effects of internal and external political efficacy and community collective efficacy as significant individual level influences on internet use for civic and political purposes. Second, group internet use—which includes new internet technologies—and group political discussion were revealed as key influences on citizens' perspectives on the helpfulness of the internet for civic and political purposes at the group level of analysis. Finally, in multilevel analysis, those recognized group level variables (group internet use and group political discussion and interests) led to positive agreement with the following statements: 1) the internet has helped me feel more connected with people like myself in the local area; 2) the internet has helped me feel more connected with a diversity of people in the local area; and 3) the internet has helped me become more involved in local issues that interest me when taking individual level variables into account. / Ph. D.

The purpose of this research was to compare results from two approaches to measuring change over time. The multilevel model (MLM) and latent growth model (LGM) were imposed and the parameter estimates were compared, along with model fit. The study came out of education and used data collected from 191 teachers as part of a professional development intervention in science, which took place over four years. There were missing data as a result of teacher attrition. Teachers reported use of reform-oriented practices (ROP) was used as the outcome, and teacher-level variables were examined for their impact on initial ROP and change in ROP from baseline to one year after the intervention. Change in ROP was examined using a piecewise change model where two linear slopes were modeled. The first slope estimated the change from baseline to T1, or the initial change after the intervention while the second slope estimated the change from T1 to T3, or the secondary change. Parameter estimates obtained from MLM and LGM for a model using the error covariance structure commonly assumed in MLM (i.e., random slopes, homogeneous level-1 variance) were nearly identical. Models with various alternative covariance structures (commonly associated with the LGM framework) were examined, and results were nearly identical. Most of the model fit information was in agreement regarding the best fitting model being the model that assumed the typical MLM error covariance structure with the exception of the standardized root mean square residual (SRMR) fit index. The results from the models demonstrated that ROP increased after participating in the first year of the intervention and this level was sustained, though did not increase significantly in subsequent years. There was more variation in ROP at baseline. This information tells us that the intervention was successful in that after participating in the intervention the teachers' used ROP more frequently. The success of the intervention did not depend on any of the predictors that we assessed, and, as a group, the teachers became more similar in their use of reform-oriented practices over time.

To increase real estate values, developers often apply designs on the land. In the case of a single family housing development, the designs are applied to the unit of subdivisions. In this study, the designs are defined as “value creation concepts,” which increase housing values at the subdivision level. The value creation concepts are classified into five categories – the sense of arrival, product mix, walkability, circulation system, and amenity. This cross-sectional study focuses on exploring the effects of value creation concepts in the subdivision. Two methodologies – the Hedonic Price Model (HPM) and the Hierarchical Linear Model (HLM) – are used to test whether or not the value creation concepts would increase or decrease single family housing values. The study sample is composed of 6,562 single family houses nested in 85 subdivisions in College Station, Texas. Data are composed of two levels: the housing level and the subdivision level. The scores of the sense of arrival were provided by sixtyone graduate students at Texas A&M University using photograph evaluations. Most structural variables were obtained from the Brazos County Appraisal District, and physical environmental variables were objectively measured using the Geographical Information System. In the both models, sense of arrival, greenway connectivity, sidewalk connectivity, and median length of cul-de-sac variables have positive effects on single family housing values while phased project, the number of accessible entrances, street density, single family density, and median length of block variables have negative effects on single family housing values. At the housing level, several structural variables (e.g. bathrooms, attached garage, porches, etc), attached to a golf course, sports facilities, network distance from the nearest elementary school, population density, and personal variables (i.e., tenure, workable age, employment) were significant (p<.05) predictors of single family housing value. Findings support that the value creation concepts have effects on increasing housing values at the subdivision level, which would provide thoughtful insights for developers in residential areas. In addition, the HLM can be used as the complement of the HPM by controlling interaction terms between housing variables and subdivision variables, or among the subdivision variables themselves.

Due to the inherently hierarchical nature of many natural phenomena, data collected rests in nested entities. As an example, students are nested in schools, school are nested in districts, districts are nested in counties, and counties are nested within states. Multilevel models provide a statistical framework for investigating and drawing conclusions regarding the influence of factors at differing hierarchical levels of analysis. The work in this paper serves as an introduction to multilevel models and their comparison to Ordinary Least Squares (OLS) regression. We overview three basic model structures: variable intercept model, variable slope model, and hierarchical linear model and illustrate each model with an example of student data. Then, we contrast the three multilevel models with the OLS model and present a method for producing confidence intervals for the regression coefficients. / text

Receiver operating characteristic (ROC) curves have been widely used in evaluation of the goodness of the diagnostic method in many study fields, such as disease diagnosis in medicine. The area under the ROC curve (AUC) naturally became one of the most used variables in gauging the goodness of the diagnosis (Mossman, Somoza 1991). Since medical diagnosis often is not dichotomous, the ROC curve and AUC need to be generalized to a multi-dimensional case. The generalization of AUC to multi-class case has been studied by many researchers in the past decade. Most recently, Nakas & Yiannoutsos (2004) considered the ordered d classes ROC analysis by only considering the sensitivities of each class. Hence, their dimension is only d. Cha (2005) considered more types of mis-classification in the ordered multiple-class case, but reduced the dimension of Ferri, at.el. from d(d-1) to 2(d-1). In this dissertation we are trying to adjust and calculate the VUS for an ordered multipleclass with Cha’s 2(d-1)-dimension method. Our methodology of finding the VUS is introduced. We present the method of adjusting and calculating VUS and their statistical inferences for the 2(d-1)-dimension. Some simulation results are included and a real example will be presented. Intellectual outcomes in pediatric brain-tumor patients were investigated in a prospective longitudinal study. The Standard-Binet Intelligence Scale-Fourth Edition (SB-IV) Standard Age Score (SAS) and Composite intelligence quotient (IQ) score are examined as cognitive outcomes in pediatric brain-tumor patients. Treatment factors, patient factors and time since diagnosis are taken into account as the risk factors. Hierarchical linear/quadratic models and Gompertz based hierarchical nonlinear growth models were applied to build linear and nonlinear longitudinal curves. We use PRESS and Volume Under the Surface (VUS) as the criterions to compare these two methods. Some model interpretations are presented in this dissertation.