Tiffany A. Whittaker

Scale Development Research A Content Analysis and Recommendations for Best Practices

The authors conducted a content analysis on new scale development articles appearing in the Journal of Counseling Psychology during 10 years (1995 to 2004). The authors analyze and discuss characteristics of the exploratory and confirmatory factor analysis procedures in these scale development studies with respect to sample characteristics, factorability, extraction methods, rotation methods, item deletion or retention, factor retention, and model fit indexes. The authors uncovered a variety of specific practices that were at variance with the current literature on factor analysis or structural equation modeling. They make recommendations for best practices in scale development research in counseling psychology using exploratory and confirmatory factor analysis.

A Beginner's Guide to Structural Equation Modeling (3rd ed.)

Randall E. Schumacker and Richard G. Lomax. New York, NY: Routledge, 2010, 536 pages,

Assessing Teacher Use of Opportunities to Respond and Effective Classroom Management Strategies: Comparisons among High- and Low-Risk Elementary Schools.

59.95 (softcover). As the popularity of structural equation modeling (SEM) grows, so does the number of introd...

Using the Modification Index and Standardized Expected Parameter Change for Model Modification

The importance of effective instruction on student academic and social achievement has been well documented. Strong classroom management and the use of high rates of opportunities to respond (OTR) have been two advocated classroom practices to positively impact student performance. This article presents an analysis of data collected across 35 general education classrooms in four elementary schools, assessing instructional variables associated with OTR. The relationship among OTR, measures of classroom management, and student work products was analyzed across Title and non-Title schools. Results indicate that teachers in the present study used components of OTR at rates similar to past research, but there were clear differences among Title I and non-Title schools. In addition, as teacher use of key instructional variables increased or decreased, other key variables posited as necessary by the literature often suffered. Implications for future research are discussed for students in high- and low-risk general education classrooms.

Examining the Factor Structure of the Self-Compassion Scale in Four Distinct Populations: Is the Use of a Total Scale Score Justified?

Model modification is oftentimes conducted after discovering a badly fitting structural equation model. During the modification process, the modification index (MI) and the standardized expected parameter change (SEPC) are 2 statistics that may be used to aid in the selection of parameters to add to a model to improve the fit. The purpose of this study was to extend the literature by examining the performance of the MI and the SEPC used independently and in conjunction with one another in terms of arriving at the correct confirmatory factor model. The results indicated that, in general, the SEPC outperformed the MI when arriving at the correct confirmatory factor model. However, they performed more similarly as factor loading size, sample size, and misspecified parameter size increased. The author provides recommendations on when the MI and SEPC perform more optimally.

Perceived discrimination and sexual precursor behaviors in Mexican American preadolescent girls: The role of psychological distress, sexual attitudes, and marianismo beliefs.

ABSTRACT This study examined the factor structure of the Self-Compassion Scale (SCS) using a bifactor model, a higher order model, a 6-factor correlated model, a 2-factor correlated model, and a 1-factor model in 4 distinct populations: college undergraduates (N = 222), community adults (N = 1,394), individuals practicing Buddhist meditation (N = 215), and a clinical sample of individuals with a history of recurrent depression (N = 390). The 6-factor correlated model demonstrated the best fit across samples, whereas the 1- and 2-factor models had poor fit. The higher order model also showed relatively poor fit across samples, suggesting it is not representative of the relationship between subscale factors and a general self-compassion factor. The bifactor model, however, had acceptable fit in the student, community, and meditator samples. Although fit was suboptimal in the clinical sample, results suggested an overall self-compassion factor could still be interpreted with some confidence. Moreover, estimates suggested a general self-compassion factor accounted for at least 90% of the reliable variance in SCS scores across samples, and item factor loadings and intercepts were equivalent across samples. Results suggest that a total SCS score can be used as an overall mesure of self-compassion.

Latent Growth Modeling With Domain-Specific Outcomes Comprised of Mixed Response Types in Intervention Studies

OBJECTIVES This study explored the relation between perceived discrimination and sexual precursor behaviors among 205 Mexican American preadolescent middle school girls. In addition, this study examined whether psychological distress and sexual attitudes mediated and whether marianismo beliefs moderated this relation. METHOD A categorical confirmatory factor analysis (CCFA) of the Marianismo Beliefs Scale (MBS) was conducted to test the factor structure with a preadolescent Mexican American population (ages 11-14). A path analysis of analytic models was then performed to examine the hypothesized relations between perceived discrimination, psychological distress, sexual attitudes, marianismo beliefs, and sexual precursor behaviors. RESULTS Results of the CCFA did not support the original 5-factor structure of the MBS for preadolescent Latina girls. However, a revised version of the MBS indicated an acceptable model fit, and findings from the path analysis indicated that perceived discrimination was both directly and indirectly linked to sexual precursor behaviors via psychological distress. Marianismo was not found to moderate the relation between perceived discrimination and sexual risk behaviors, however certain marianismo pillars were significantly negatively linked with sexual attitudes and precursor behaviors. CONCLUSIONS This study underscores the importance of psychological distress in the perceived discrimination and sexual precursor link as well as the compensatory aspects of marianismo against sexual precursor behaviors in Mexican American preadolescent girls. (PsycINFO Database Record

Quantitative Approaches to Group Research: Suggestions for Best Practices

OBJECTIVE When several continuous outcome measures of interest are collected across time in experimental studies, the use of standard statistical procedures, such as multivariate analysis of variance or growth curve modeling, can be properly used to assess treatment effects. However, when data consist of mixed responses (e.g., continuous and ordered categorical [ordinal] responses), traditional modeling approaches are no longer appropriate. The purpose of this article is to illustrate the use of a more suitable modeling procedure when mixed responses are collected in longitudinal intervention studies. METHOD Problems with traditional analyses of such data are discussed, as are potential advantages provided by the proposed modeling approach. The application of the multiple-domain latent growth modeling approach with mixed responses is illustrated for experimental designs with data from the SeniorWISE study (McDougall et al., 2010). This multisite randomized trial assessed memory functioning of 265 elderly adults across a 26-month period after receiving either a memory or health promotion training program. RESULTS The latent growth models illustrated allow one to examine treatment effects on the growth of multiple mixed outcomes while incorporating associations among multiple responses, which allows for better missing data treatment, greater power, and more accurate control of Type I error. The interpretation of parameters of interest and treatment effects is discussed using the SeniorWISE data. CONCLUSIONS Multiple-domain latent growth modeling with mixed responses is a flexible statistical modeling tool that can have substantial benefits for applied researchers. As such, the use of this modeling approach is expected to increase.

The Performance of IRT Model Selection Methods With Mixed-Format Tests

Rigorous scholarship is essential to the continued growth of group work, yet the unique nature of this counseling specialty poses challenges for quantitative researchers. The purpose of this proposal is to overview unique challenges to quantitative research with groups in the counseling field, including difficulty in obtaining large sample sizes and the violation of the independence assumption. Current practice is illustrated by referencing recent quantitative research in The Journal for Specialists in Group Work, and recommendations are provided for best practices in designing, analyzing, and reporting quantitative research.

Detecting Appropriate Trajectories of Growth in Latent Growth Models: The Performance of Information-Based Criteria

When tests consist of multiple-choice and constructed-response items, researchers are confronted with the question of which item response theory (IRT) model combination will appropriately represent the data collected from these mixed-format tests. This simulation study examined the performance of six model selection criteria, including the likelihood ratio test, Akaike’s information criterion (AIC), corrected AIC, Bayesian information criterion, Hannon and Quinn’s information criterion, and consistent AIC, with respect to correct model selection among a set of three competing mixed-format IRT models (i.e., one-parameter logistic/partial credit [1PL/PC], two-parameter logistic/generalized partial credit [2PL/GPC], and three-parameter logistic/generalized partial credit [3PL/GPC]). The criteria were able to correctly select less parameterized IRT models, including the PC, 1PL, and 1PL/PC models. In contrast, the criteria were less able to correctly select more parameterized IRT models, including the GPC, 3PL, and 3PL/GPC models. Implications of the findings and recommendations are discussed.