S. Natasha Beretvas

A Reliability Generalization Study of the Marlowe-Crowne Social Desirability Scale

A reliability generalization (RG) study was conducted for the Marlowe-Crowne Social Desirability Scale (MCSDS). The MCSDS is the most commonly used tool designed to assess social desirability bias (SDB). Several short forms, consisting of items from the original 33-item version, are in use by researchers investigating the potential for SDB in responses to other scales. These forms have been used to measure a wide array of populations. Using a mixed-effects model analysis, the predicted score reliability for male adolescents was.53 and the reliability for men’sresponseswaslower than that for women’s. Suggestions are made concerning the necessity for further psychometric evaluations of the MCSDS.

Validation of Scores on the Marlowe-Crowne Social Desirability Scale and the Balanced Inventory of Desirable Responding:

The Marlowe-Crowne Social Desirability Scale (MCSDS), the most commonly used social desirability bias (SDB) assessment, conceptualizes SDB as an individual’s need for approval. The Balanced Inventory of Desirable Responding (BIDR) measures SDB as two separate constructs: impression management and self-deception. Scores on SDB scales are commonly used to validate other measures although insufficiently validated themselves. This study used college students’ responses to the MCSDS and the BIDR to investigate their factorial validity. Using confirmatory factor analysis, neither a one-nor a two-factor model was found to be strongly supported. It is recommended that researchers be cautious when using scores on these SDB scales until their dimensionality is better understood.

The Role of Self-compassion in Romantic Relationships

Self-compassion (SC) involves being kind to oneself when confronting personal inadequacies or situational difficulties, framing the imperfection of life in terms of common humanity, and being mindful of negative emotions so that one neither suppresses nor ruminates on them. The current study explored whether being self-compassionate is linked to healthier romantic relationship behavior, such as being more caring and supportive rather than controlling or verbally aggressive with partners. A total of 104 couples participated in the study, with self-reported SC levels being associated with partner reports of relationship behavior. Results indicated that self-compassionate individuals displayed more positive relationship behavior than those who lacked SC. SC was also a stronger predictor of positive relationship behavior than trait self-esteem (SE) or attachment style. Finally, partners were able to accurately report on each others SC levels, suggesting that SC is an observable trait.

The Impact of Inappropriate Modeling of Cross-Classified Data Structures

Cross-classified random effects modeling (CCREM) is used to model multilevel data from nonhierarchical contexts. These models are widely discussed but infrequently used in social science research. Because little research exists assessing when it is necessary to use CCREM, 2 studies were conducted. A real data set with a cross-classified structure was analyzed by comparing parameter estimates when ignoring versus modeling the cross-classified data structure. A follow-up simulation study investigated potential factors affecting the need to use CCREM. Results indicated that when the structure is ignored, fixed-effect estimates were unaffected, but standard error estimates associated with the variables modeled incorrectly were biased. Estimates of the variance components also displayed bias, which was related to several study factors.

Evaluating Collaborative Learning and Community

The goal of this study was to validate measures and assess the effects of collaborative group-learning methods in real classrooms on 3 specific dependent variables: feelings of campus connectedness, academic classroom community, and effective group processing (2 factors). Confirmatory factor analyses were conducted to evaluate a 4-factor model. Using hierarchical linear modeling techniques, results indicated that campus connectedness and collaborative learning (compared with no collaborative learning) predicted positive academic classroom community. For classes using more formal cooperative group work, campus connectedness and group processingndash;evaluation predicted positive academic classroom community. Suggestions for further applications of the measures are discussed.

A review of meta-analyses of single-subject experimental designs: Methodological issues and practice

Several metrics have been suggested for summarizing results from single-subject experimental designs. This study briefly reviews the most commonly used metrics, noting their methodological limitations. This study also includes a synthesis of recent meta-analyses, describing which metrics were used and how meta-analysts handled dependence in the form of multiple treatments, outcomes, and participants per study. Guidelines for future methodological research and for single-subject experimental design meta-analysts are provided. Source of funding: Preparation of this article was supported by a grant from the Institute of Education Sciences, U.S. Department of Education. However, the opinions expressed do not express the opinions of this agency.

Teachers' preparation to teach reading and their experiences and practices in the first three years of teaching

The study reported in this article focused on the preparation of elementary preservice teachers to teach reading and on their first 3 years of teaching in schools. Graduates of 8 programs judged as “excellent” by an expert review panel participated in this study. The research was guided by 2 questions: (1) What effects do participation in and completion of an excellent reading teacher education program have on the experiences of teachers as they enter schools? and (2) How does teachers’ preparation relate to their teaching practices? We used quantitative and qualitative research methods to explore these questions. The research design was quasi‐experimental, with the teacher education program considered as the intervening variable. Comparison groups for graduates of the excellent programs included same‐school, highly experienced teachers as well as same‐school, same‐years experienced teachers. Data were collected over 3 years. Results suggested that participation in a high‐quality teacher preparation program had a positive influence on the transition of teachers entering the profession and on the adoption of effective teaching practices by these teachers. Graduates of the excellent programs were more effective than teachers in the comparison groups in creating and engaging their students with a high‐quality literacy environment.

The Online and Face-to-Face Counseling Attitudes Scales: A Validation Study.

Abstract This article reports on the development of measures of attitudes toward online and face-to-face counseling Overall, participants expressed more favorable evaluations of face-to-face counseling than of online counseling. Significant correlations were found between online and face-to-face counseling with traditional help seeking attitudes, comfort with e-mail, and interest in various counseling services. Counseling and research considerations are reviewed.

Meta-analytic methods of pooling correlation matrices for structural equation modeling under different patterns of missing data

Three methods of synthesizing correlations for meta-analytic structural equation modeling (SEM) under different degrees and mechanisms of missingness were compared for the estimation of correlation and SEM parameters and goodness-of-fit indices by using Monte Carlo simulation techniques. A revised generalized least squares (GLS) method for synthesizing correlations, weighted-covariance GLS (W-COV GLS), was compared with univariate weighting with untransformed correlations (univariate r) and univariate weighting with Fishers z-transformed correlations (univariate z). These 3 methods were crossed with listwise and pairwise deletion. Univariate z and W-COV GLS performed similarly, with W-COV GLS providing slightly better estimation of parameters and more correct model rejection rates. Missing not at random data produced high levels of relative bias in correlation and model parameter estimates and higher incorrect SEM model rejection rates. Pairwise deletion resulted in inflated standard errors for all synthesis methods and higher incorrect rejection rates for the SEM model with univariate weighting procedures.

From a single-level analysis to a multilevel analysis of single-case experimental designs ☆

Multilevel modeling provides one approach to synthesizing single-case experimental design data. In this study, we present the multilevel model (the two-level and the three-level models) for summarizing single-case results over cases, over studies, or both. In addition to the basic multilevel models, we elaborate on several plausible alternative models. We apply the proposed models to real datasets and investigate to what extent the estimated treatment effect is dependent on the modeling specifications and the underlying assumptions. By considering a range of plausible models and assumptions, researchers can determine the degree to which the effect estimates and conclusions are sensitive to the specific assumptions made. If the same conclusions are reached across a range of plausible assumptions, confidence in the conclusions can be enhanced. We advise researchers not to focus on one model but conduct multiple plausible multilevel analyses and investigate whether the results depend on the modeling options.