Introduction to the Special Section on Structural Equation Modeling.

Structural equation modeling (SEM) is a frequently used data-analytic technique in psychopathology research. This popularity is due to the unique capabilities and broad applicability of SEM and to recent advances in model and software development. Unfortunately, the popularity and accessibility of SEM is matched by its complexities and ambiguities. Thus, users are often faced with difficult decisions regarding a variety of issues. This special section is designed to increase the effective use of SEM by reviewing recently developed modeling capabilities, identifying common problems in application, and recommending appropriate strategies for analysis and evaluation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Clinical and Applied Research Techniques.

The use of instruments by applied psychologists is universal though seldom recognized. In this section, an attempt has been made to cover several recent advances in the clinical and applied areas of psychology. Topics range from evaluations of biofeedback alpha devices, the use of computers in profile analysis, interviewing, personality assessment, and medical/clinical data processing and simulation to radio telemetry techniques of use to clinical and applied psychologists. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Introduction to the Special Section on Theoretical Models and Conceptual Analyses: Theory in Applied Psychology: Lessons (Re)Learned.

The Journal of Applied Psychology's call for theoretical models and conceptual analyses brought a terrific response. The editors introduce the special section and comment on lessons learned, or perhaps re-learned, about developing and writing theory in applied psychology. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Hierarchical linear modeling analyses of the NEO-PI-R Scales in the Baltimore Longitudinal Study of Aging.

The authors examined age trends in the 5 factors and 30 facets assessed by the Revised NEO Personality Inventory in Baltimore Longitudinal Study of Aging data (N = 1,944; 5,027 assessments) collected between 1989 and 2004. Consistent with cross-sectional results, hierarchical linear modeling analyses showed gradual personality changes in adulthood: a decline in Neuroticism up to age 80, stability and then decline in Extraversion, decline in Openness, increase in Agreeableness, and increase in Conscientiousness up to age 70. Some facets showed different curves from the factor they define. Birth cohort effects were modest, and there were no consistent Gender × Age interactions. Significant nonnormative changes were found for all 5 factors; they were not explained by attrition but might be due to genetic factors, disease, or life experience. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Evaluating model fit for growth curve models: Integration of fit indices from SEM and MLM frameworks.

Evaluating overall model fit for growth curve models involves 3 challenging issues. (a) Three types of longitudinal data with different implications for model fit may be distinguished: balanced on time with complete data, balanced on time with data missing at random, and unbalanced on time. (b) Traditional work on fit from the structural equation modeling (SEM) perspective has focused only on the covariance structure, but growth curve models have four potential sources of misspecification: within-individual covariance matrix, between-individuals covariance matrix, marginal mean structure, and conditional mean structure. (c) Growth curve models can be estimated in both the SEM and multilevel modeling (MLM) frameworks; these have different emphases for the evaluation of model fit. In this article, the authors discuss the challenges presented by these 3 issues in the calculation and interpretation of SEM- and MLM-based fit indices for growth curve models and conclude by identifying some lines for future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Applied Research: Variations on a Theme.

Describes problems in applying research to solve practical problems. After describing problems with applied research the author notes that some situationally centered research is paying off. The author contents that a program of research on research translations is called for. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Introduction to functional data analysis.

Psychologists and behavioural scientists are increasingly collecting data that are drawn from continuous underlying processes. We describe a set of quantitative methods, Functional Data Analysis (FDA), which can answer a number of questions that traditional statistical approaches cannot. These methods are applicable for analyzing many datasets that are common in experimental psychology, including time series data, repeated measures, and data distributed over time or space as in neuroimaging experiments. The primary advantage of FDA is that it allows the researcher to ask questions about when in a time series differences may exist between two or more sets of observations. We discuss functional correlations, principal components, the derivatives of functional curves, and analysis of variances models. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Introduction to the Special Section on Metric in Meta-Analysis.

A key issue for meta-analysts is how to represent study outcomes--in other words, what is the best metric for study outcomes? This introduction describes four articles in a special section on metric in meta-analysis. Do meta-analyses require standardized measures of study outcome? C. F. Bond, W. L. Wiitala, and F. D. Richard (2003) argue that standardization is often not needed and can obscure results. Another aspect of scaling outcomes is dichotomization. J. Sánchez-Meca, F. Marín-Martínez, and S. Chacón-Moscoso (2003) compare estimators appropriate when a meta-analysis includes treatment-control studies with dichotomized outcomes. Two articles deal with additional design complexities. R. Gillett (2003) describes mean-difference estimators, outlining indices comparable to effects from the t test. S. Olejnik and J. Algina (2003) provide a formula for generalized eta squared and omega squared statistics that are comparable across research designs. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ethical Perspectives on Qualitative Research in Applied Psychology.

The present article explores ethical issues that emerge in qualitative research conducted by applied psychologists. The utility and relevance of the Ethical Principles of Psychologists and Code of Conduct (American Psychological Association, 2002) for qualitative research are examined. The importance of psychology's fiduciary relationship with research participants is presented as the basis for an ethical stance of "trustworthiness." A scientist-practitioner perspective on research ethics is advanced, based on the argument that psychology's social role carries obligations that differ from those of other social science disciplines that conduct qualitative research. Dilemmas that are likely to emerge in qualitative research are discussed, with particular attention to competence, multiple relationships, confidentiality, and informed consent. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Use of Latent Trajectory Models in Psychopathology Research.

Despite the recent surge in the development of powerful modeling strategies to test questions about individual differences in stability and change over time, these methods are not currently widely used in psychopathology research. In an attempt to further the dissemination of these new methods, the authors present a pedagogical introduction to the structural equation modeling based latent trajectory model, or LTM. They review several different types of LTMs, discuss matching an optimal LTM to a given question of interest, and highlight several issues that might be particularly salient for research in psychopathology. The authors augment each section with a review of published applications of these methods in psychopathology-related research to demonstrate the implementation and interpretation of LTMs in practice. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Latent variable analyses of age trends of cognition in the Health and Retirement Study, 1992-2004.

The present study was conducted to better describe age trends in cognition among older adults in the longitudinal Health and Retirement Study (HRS) from 1992 to 2004 (N = 17,000). The authors used contemporary latent variable models to organize this information in terms of both cross-sectional and longitudinal inferences about age and cognition. Common factor analysis results yielded evidence for at least 2 common factors, labeled Episodic Memory and Mental Status, largely separable from vocabulary. Latent path models with these common factors were based on demographic characteristics. Multilevel models of factorial invariance over age indicated that at least 2 common factors were needed. Latent curve models of episodic memory were based on age at testing and showed substantial age differences and age changes, including impacts due to retesting as well as several time-invariant and time-varying predictors. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The multilevel latent covariate model: A new, more reliable approach to group-level effects in contextual studies.

In multilevel modeling (MLM), group-level (L2) characteristics are often measured by aggregating individual-level (L1) characteristics within each group so as to assess contextual effects (e.g., group-average effects of socioeconomic status, achievement, climate). Most previous applications have used a multilevel manifest covariate (MMC) approach, in which the observed (manifest) group mean is assumed to be perfectly reliable. This article demonstrates mathematically and with simulation results that this MMC approach can result in substantially biased estimates of contextual effects and can substantially underestimate the associated standard errors, depending on the number of L1 individuals per group, the number of groups, the intraclass correlation, the sampling ratio (the percentage of cases within each group sampled), and the nature of the data. To address this pervasive problem, the authors introduce a new multilevel latent covariate (MLC) approach that corrects for unreliability at L2 and results in unbiased estimates of L2 constructs under appropriate conditions. However, under some circumstances when the sampling ratio approaches 100%, the MMC approach provides more accurate estimates. Based on 3 simulations and 2 real-data applications, the authors evaluate the MMC and MLC approaches and suggest when researchers should most appropriately use one, the other, or a combination of both approaches. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Methodology for identifying specific psychological deficits: Introduction to the Special Section.

A long-standing problem in psychopathology research is establishing that patterns of differences between groups reflects differences of underlying constructs and not artifacts of research design, measurement, or analysis. This introduction provides a context for 4 articles that consider several controversial issues regarding this problem and presents a précis. Although these articles focus on schizophrenia, it is noted how the issues are of more general relevance to psychopathology researchers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Special Section: Philosophy of Science and Counseling Research: Editor's Introduction.

Introduces readers to a special subsection on philosophy of science and counseling research and provides an overview of the articles. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Longitudinal relationships of levels of language in writing and between writing and reading in grades 1 to 7.

Longitudinal structural equation modeling was used to evaluate longitudinal relationships across adjacent grade levels 1 to 7 for levels of language in writing (Model 1, subword letter writing, word spelling, and text composing) or writing and reading (Model 2, subword letter writing and word spelling and reading; Model 3, word spelling and reading and text composing and comprehending). Significant longitudinal relationships were observed within and across levels of language: spelling to spelling and spelling to composing (Grades 1 to 7), Models 1 and 3, and composing to spelling (Grades 3 to 6, Model 1; Grades 4 to 6, Model 3); spelling to word reading and word reading to spelling (Grades 2 to 7), Models 2 and 3; spelling to word reading (Grade 1), Model 2, and word reading to spelling (Grade 1), Model 3; composition to comprehension (Grades 3 to 5), Model 3; comprehension to composition (Grades 2 to 6), Model 3; and comprehension to word reading (Grades 1 to 6), Model 3. Results are discussed in reference to the levels of language in translating ideas into written language and integrating writing and reading. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Review of Qualitative Research Methods for Psychologists: Introduction through Empirical Studies.

Reviews the book, Qualitative Research Methods for Psychologists: Introduction through Empirical Studies edited by Constance T. Fischer (2006). This book is intended as an introductory textbook for psychology students and psychologists who have been trained in traditional psychological research methods with the goal of providing an orientation to qualitative research frameworks and how they are applied to the many research questions that might be considered by psychologists. The book begins with a useful introductory chapter by the editor that provides a historical overview of the emergence of psychology as a science concerned primarily with determining causal relationships. There are 13 chapters in the body of the book and they are gathered into three parts: Clinical Practices, Affective and Cognitive Processes, and Life Situations. The book ends with a Question and Responses chapter by the editor that covers many of the questions novice qualitative researchers often have about qualitative research. The last section is a detailed Glossary of terms that are significant in understanding qualitative research. There is much in this book to recommend it as an introductory book on qualitative research for graduate students and beginning qualitative researchers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Introduction to the Special Section on Dissemination: Dissemination Research and Research Dissemination: How Can We Close the Gap?

One of the greatest challenges facing health promotion and disease prevention is translating research findings into evidence-based public health and clinical practices that are actively disseminated and widely adopted. Despite the tremendous strides made in developing effective disease prevention and control programs, there has been little study of effective dissemination of evidence-based programs to and adoption by community, public health, and clinical practice settings. This special section provides a venue in which to highlight exemplary dissemination research efforts while also identifying limitations in research to date and framing important future research questions. This issue establishes a resource for investigators interested in dissemination research, with relevance to health psychology. In this sense, it can serve as a benchmark by which to examine subsequent progress. The 6 articles reflect the state of the science in dissemination research for the promotion and adoption of health behavior change interventions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An introduction to using structural equation models in rehabilitation psychology.

Objective: To provide an overview of structural equation modeling (SEM) using an example drawn from the rehabilitation psychology literature. Design: To illustrate the 5 steps in SEM (model specification, identification, estimation methods, interpretation of results, and model modification), an example is presented, with details on determining whether alternative models result in a significant improvement to fit to the observed data. Data are from a sample of 274 people with spinal cord injury. Issues commonly encountered in preparing data for SEM analyses (e.g., missing data, nonnormality) are reviewed, as is the debate surrounding some aspects of SEM (e.g., acceptable sample size). Conclusion: SEM can be a powerful procedure for empirically representing complex and sophisticated theoretical models of interest to rehabilitation psychologists. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Testing Mediational Models With Longitudinal Data: Questions and Tips in the Use of Structural Equation Modeling.

R. M. Baron and D. A. Kenny (1986; see record 1987-13085-001) provided clarion conceptual and methodological guidelines for testing mediational models with cross-sectional data. Graduating from cross-sectional to longitudinal designs enables researchers to make more rigorous inferences about the causal relations implied by such models. In this transition, misconceptions and erroneous assumptions are the norm. First, we describe some of the questions that arise (and misconceptions that sometimes emerge) in longitudinal tests of mediational models. We also provide a collection of tips for structural equation modeling (SEM) of mediational processes. Finally, we suggest a series of 5 steps when using SEM to test mediational processes in longitudinal designs: testing the measurement model, testing for added components, testing for omitted paths, testing the stationarity assumption, and estimating the mediational effects. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Introduction to the special section on cognitive plasticity in the aging mind.

Decades of cognitive aging research have led to a picture of the aging mind that is primarily characterized by gradual, though relatively broad, cognitive decline across the life span. Until recently, relatively little attention has been devoted to the question of whether there are ways to slow down, if not stop, this decline. With the special section on cognitive plasticity in the aging mind, we respond to what seems to be a beginning of the reversal of this trend (e.g., Kramer & Willis, 2002). In this short introduction, the author provides some context and a preview of the articles that appear in the special section. (PsycINFO Database Record (c) 2010 APA, all rights reserved)