Violence: An annotated bibliography of selected publications and resources

Reducing violence-related injuries and deaths among youth requires an integrated community-based approach, involving policy, education, legal and regulatory, and environmental modification strategies. Developing violence-prevention programs demands an understanding of the problem, knowledge of existing programs and their effectiveness, technical expert assistance, and human and material resources. This annotated bibliography of selected publications and resources relates to violence and violence prevention. The purpose of the bibliography is to provide a first point-of-entry for using the literature and for identifying and locating additional resources. The publications include a collection of research reports, conference proceedings and their background papers, and articles exploring issues and reviewing prevention strategies and resources. Resource entries identify federal agencies, academic centers, and projects that provide a range of services and assistance.     

Globalisation: An annotated bibliography for the readers of Assessment in Education

This paper takes the form of an annotated bibliography providing a synopsis of the work of some influential writers on globalisation, and presenting an indication of the wide-ranging nature of debate in the field. The selection of works is intended to inform and interest readers with a background in education and assessment.     

Sewall wright on the method of path coefficients: An annotated bibliography

When Dudley Duncan and others became interested in linear causal models, they discovered a genetic biologist had laid down the groundwork for them over nearly a 50‐year period. This annotated bibliography covers Sewall Wright's development of the method of path coefficients.     

Confirmation bias in structural equation modeling

In this article, a theoretical and philosophical revision of the concept of fit in structural equation modeling and its relation to a confirmation bias is developed. The neutral character of the fit indexes regarding this issue is argued, yielding the conclusion that the creation of new indexes is not a viable protection against confirmation bias. This protection relies on the model modification strategy and the behavior of scientists, rather than on mathematical or computational statistics. The differentiation between two sets of overidentifying constraints and two dimensions for nested models is introduced, leading to a general model‐modification strategy based on the framework of Popper's view of science.     

Using structural equation modeling to fit models incorporating principal components

The aim of this article is to consider models incorporating principal components from the perspective of structural equation modeling. These models include the principal component analysis of patterned matrices, multiple analysis of variance based on principal components, and multigroup principal component analysis. We demonstrate that these models can be fit readily using the programs LISREL 8 and Mx. The models and certain extensions are discussed, and several illustrations are given.     

Using structural equation modeling techniques to evaluate HIV risk models

Structural equation modeling (SEM) techniques were used to compare 5 methods of assessing HIV/AIDS sexual risk in a large prediction model. These were: (a) multiple measures; (b) a single latent factor; (c) modifying the computation of the dependent variables used in Methods 1 and 2 to weight sexual encounters by specific partner risk; (d) use of risk composites, obtained by multiplying number of sexual partners by number of occasions of unprotected sex; and (e) use of risk indexes that assign a number based on responses to general questions about risk behaviors. Data from 452 at‐risk women from a New England community were analyzed in 5 versions of an HIV/AIDS sexual risk prediction model. Models were compared in terms of SEM empirical fit indexes (x² [df], average absolute standardized residuals, and Comparative Fit Index); significant paths, explained variance, theoretical fit, and simplicity. Results indicate that: (a) multiple measures and latent factor models are preferable to all others by each of the standards of comparison, (b) in the composite dependent variable models, including information about the partners' number of partners provided little additional explained variance beyond knowing the number of occasions of unprotected sex, and (c) dependent measures that did not remain close to Centers for Disease Control criteria may not be adequately predicting HIV/AIDS sexual risk. Several recommendations are presented for selecting an appropriate conceptualization of HIV/AIDS sexual risk.     

Errors of inference in structural equation modeling

Although structural equation modeling (SEM) is one of the most comprehensive and flexible approaches to data analysis currently available, it is nonetheless prone to researcher misuse and misconceptions. This article offers a brief overview of the unique capabilities of SEM and discusses common sources of user error in drawing conclusions from these analyses. We make recommendations to guide proper analytical practices and appropriate inferences and provide references for more advanced study. © 2007 Wiley Periodicals, Inc. Psychol Schs 44: 461–470, 2007.     

Issues in applied structural equation modeling research

When using the popular structural equation modeling (SEM) methodology, the issues of sample size, method of parameter estimation, assessment of model fit, and capitalization on chance are of great importance in the process of evaluating the results of an empirical study. We focus first on implications of the large‐sample theory underlying applications of the methodology. The utility for applied contexts of the asymptotically distribution‐free parameter estimation and model testing method is discussed next. We then argue for wider use of a recently developed, non conventional model‐fit assessment strategy in SEM. We conclude by discussing the issue of capitalization on chance, primarily in situations in which exploratory and confirmatory analyses are conducted on the same data set.     

Teacher self-efficacy,instructional quality,and student motivational beliefs: An analysis using multilevel structural equation modeling

Teacher self-efficacy (TSE) is one of the most salient motivational characteristics that is assumed to affect teachers’ instructional quality and student motivational beliefs. However, discussions of these associations have primarily been often primarily conceptual and/or based on empirical research that has suffered from methodological shortcomings. Therefore, the aim of this study was to examine the relationships between TSE, instructional quality (i.e., classroom management, cognitive activation, and supportive climate) and student motivational beliefs (i.e., self-efficacy and intrinsic motivation) by using responses from both teachers and students and implementing a sophisticated doubly latent multilevel structural equation modeling approach. A total of 94 high school teachers and their 2087 students participated in the study. The results demonstrated that, at the class level, TSE was positively related to the three dimensions of instructional quality but not to student motivational beliefs. As expected, instructional quality was positively related to student motivational beliefs.     

Morphological awareness and bilingual word learning: a longitudinal structural equation modeling study

This longitudinal study examined the contribution of morphological awareness to bilingual word learning of Malay–English bilingual children in Singapore where English is the medium of instruction. Participants took morphological awareness and lexical inference tasks in both English and Malay twice with an interval of about half a year, the first time at the end of Grade 3 (Time 1) and the second time at the end of the first semester of Grade 4 (Time 2). Structural equation modeling (SEM) analyses revealed that within both languages, morphological awareness significantly predicted lexical inference at Time 1 as well as Time 2, and the contribution also became strengthened over time. Cross-linguistic SEM analyses showed that concurrently at both Time 1 and Time 2, English morphological awareness only had a significant indirect effect on Malay lexical inference. The exact indirect relationships, however, varied between Time 1 and Time 2. In addition, an indirect effect of Time 1 English morphological awareness on Time 2 Malay lexical inference also surfaced. These findings suggest concurrent as well as longitudinal cross-linguistic transfer of morphological awareness from English to Malay.     

Structural equation modeling: Back to basics

Major technological advances incorporated into structural equation modeling (SEM) computer programs now make it possible for practitioners who are basically unfamiliar with the purposes and limitations of SEM to use this tool within their research contexts. The current move by program developers to market more user friendly software packages is a welcomed trend in the social and behavioral science research community. The quest to simplify the data analysis step in the research process has—at least with regard to SEM—created a situation that allows practitioners to apply SEM but forgetting, knowingly ignoring, or most dangerously, being ignorant of some basic philosophical and statistical issues that must be addressed before sound SEM analyses should be conducted. This article focuses on some of the almost forgotten topics taken here from each step in the SEM process: model conceptualization, identification and parameter estimation, and data‐model fit assessment and model modification. The main objective is to raise awareness among researchers new to SEM of a few basic but key philosophical and statistical issues. These should be addressed before launching into any one of the new generation of SEM software packages and being led astray by the seemingly irresistible temptation to prematurely start “playing” with the data.     

What contributes to low achievement of middle school students: Evidence from multigroup structural equation modeling

The authors' purpose was to examine the degree to which low achievement is related to ontogenetic factors (i.e., personal psychological traits expressed as attention and depression) or microsystemic factors (i.e., socioeconomic status, parenting, relationship with peers and teachers), using a total of 721 middle school students in South Korea. Based on the percentile rank, low-achieving students (bottom 15%; n = 323) and high-achieving students (top 15%; n = 398) were grouped, and a multigroup structural equation modeling was employed to determine which ecological factor(s) contribute to predict low achievement of middle school students. Results from multigroup structural equation modeling showed that 3 of the 6 ecological and ontological factors had significant direct or indirect effect on low achievement: socioeconomic status (direct effect), attention (direct effect), parenting (indirect effect). The findings are discussed in terms of the intertwined influences of ecological factors on low achievement, finally leading to the discussion on the limitations and future directions for research.     

The annotated bibliography and citation behavior: enhancing student scholarship in an undergraduate biology course

Contemporary undergraduates in the biological sciences have unprecedented access to scientific information. Although many of these students may be savvy technologists, studies from the field of library and information science consistently show that undergraduates often struggle to locate, evaluate, and use high-quality, reputable sources of information. This study demonstrates the efficacy and pedagogical value of a collaborative teaching approach designed to enhance information literacy competencies among undergraduate biology majors who must write a formal scientific research paper. We rely on the triangulation of assessment data to determine the effectiveness of a substantial research paper project completed by students enrolled in an upper-level biology course. After enhancing library-based instruction, adding an annotated bibliography requirement, and using multiple assessment techniques, we show fundamental improvements in students' library research abilities. Ultimately, these improvements make it possible for students to more independently and effectively complete this challenging science-based writing assignment. We document critical information literacy advances in several key areas: student source-type use, annotated bibliography enhancement, plagiarism reduction, as well as student and faculty/librarian satisfaction.     

Model specification searches in structural equation modeling using tabu search

This article introduces an alternative structural equation modeling (SEM) specification search approach that is based on the Tabu search procedure. Using data with known structure, the performance of the Tabu search is illustrated. The results demonstrate the capabilities of the Tabu search procedure for conducting specification searches in SEM.