Wen-Juo Lo

Evaluation of Parallel Analysis Methods for Determining the Number of Factors.

Population and sample simulation approaches were used to compare the performance of parallel analysis using principal component analysis (PA-PCA) and parallel analysis using principal axis factoring (PA-PAF) to identify the number of underlying factors. Additionally, the accuracies of the mean eigenvalue and the 95th percentile eigenvalue criteria were examined. The 95th percentile criterion was preferable for assessing the first eigenvalue using either extraction method. In assessing subsequent eigenvalues, PA-PCA tended to perform as well as or better than PA-PAF for models with one factor or multiple minimally correlated factors; the relative performance of the mean eigenvalue and the 95th percentile eigenvalue criteria depended on the number of variables per factor. PA-PAF using the mean eigenvalue criterion generally performed best if factors were more than minimally correlated or if one or more strong general factors as well as group factors were present.

Becoming Data Driven: The Influence of Teachers’ Sense of Efficacy on Concerns Related to Data-Driven Decision Making

Data-driven decision-making (DDDM) reform has proven to be an effective means for improving student learning. However, little DDDM reform has happened at the classroom level, and little research has explored variables that influence teacher adoption of DDDM. The authors propose a model in which teachers’ sense of efficacy for the skills that support classroom-level DDDM and DDDM anxiety significantly influenced teachers’ DDDM efficacy, which then influenced collaboration concerns that influenced refocusing concerns. The authors used structural equation modeling to analyze data on 537 teachers in order to validate this hypothesized model. Results supported this model and are discussed.

Revisiting the Motivated Strategies for Learning Questionnaire: A Theoretical and Statistical Reevaluation of the Metacognitive Self-Regulation and Effort Regulation Subscales

The Motivated Strategies for Learning Questionnaire (MSLQ) has dominated self-regulated learning research since the early 1990s. In this study, the two MSLQ subscales specifically designed to assess self-regulation—Metacognitive Self-Regulation subscale and Effort Regulation subscale—were examined. Results indicated that the structure of the two scales is not supported by the original data reported by Pintrich, Smith, Garcia, and McKeachie in 1991 or new data. Statistical and theoretical analyses supported two modified scales, the General Strategies for Learning scale and the Clarification Strategies for Learning scale, that assess academic self-regulation from the original MSLQ items. The statistical and theoretical analyses, results, and modified scales are discussed.

A Proposed Solution to the Problem With Using Completely Random Data to Assess the Number of Factors With Parallel Analysis

A number of psychometricians have argued for the use of parallel analysis to determine the number of factors. However, parallel analysis must be viewed at best as a heuristic approach rather than a mathematically rigorous one. The authors suggest a revision to parallel analysis that could improve its accuracy. A Monte Carlo study is conducted to compare revised and traditional parallel analysis approaches. Five dimensions are manipulated in the study: number of observations, number of factors, number of measured variables, size of the factor loadings, and degree of correlation between factors. Based on the results, the revised parallel analysis method, using principal axis factoring and the 95th percentile eigenvalue rule, offers promise.

Determinants of Student and Parent Satisfaction at a Cyber Charter School

ABSTRACT Research indicates that in traditional public schools the subjective well-being of students and parents varies by gender, race, and special education status. Prior studies suggest that general education students are more satisfied with their schooling than special education students, that female students have greater satisfaction with their schooling than male students, and that Caucasian and Latino students report greater school satisfaction than African American students. No prior research has studied parental and student subjective well-being in a cyber environment. The authors investigate parental and student subjective well-being in a cyber charter school, using a student (n = 269; 53.7% response rate) and parent (n = 232; 48.7% response rate) survey. They find statistically significant differences in subjective well-being across demographic groups of students, and also significantly higher satisfaction among special education students in the cyber school environment. Implications are discussed.

Investigating the Sensitivity of Goodness-of-Fit Indices to Detect Measurement Invariance in a Bifactor Model

A Monte Carlo simulation study was conducted to evaluate the sensitivities of the likelihood ratio test and five commonly used delta goodness-of-fit (ΔGOF) indices (i.e., ΔGamma, ΔMcDonald’s, ΔCFI, ΔRMSEA, and ΔSRMR) to detect a lack of metric invariance in a bifactor model. Experimental conditions included factor loading differences, location and number of noninvariant items, and sample size. The results indicated all ΔGOF indices held Type I error to a minimum and overall had adequate power for the study. For detecting the violation of metric invariance, only ΔGamma and ΔCFI, in addition to Δχ2, are recommended to use in the bifactor model with values of −.016 to −.023 and −.003 to −.004, respectively. Moreover, in the variance component analysis, the magnitude of the factor loading differences contributed the most variation to all ΔGOF indices, whereas sample size affected Δχ2 the most.

Type I and Type II Error Rates and Overall Accuracy of the Revised Parallel Analysis Method for Determining the Number of Factors

Traditional parallel analysis (T-PA) estimates the number of factors by sequentially comparing sample eigenvalues with eigenvalues for randomly generated data. Revised parallel analysis (R-PA) sequentially compares the kth eigenvalue for sample data to the kth eigenvalue for generated data sets, conditioned on k− 1 underlying factors. T-PA and R-PA are conceptualized as stepwise hypothesis-testing procedures and, thus, are alternatives to sequential likelihood ratio test (LRT) methods. We assessed the accuracy of T-PA, R-PA, and LRT methods using a Monte Carlo approach. Although no method was uniformly more accurate across all 180 conditions, the PA approaches outperformed LRT methods overall. Relative to T-PA, R-PA tended to perform better within the framework of hypothesis testing and to evidence greater accuracy in conditions with higher factor loadings.

The Southern states: NPs made an impact in rural and healthcare shortage areas

Purpose:To investigate the distribution of nurse practitioners (NPs) in the U.S. Southern region with a focus on rural and underserved areas. Described in this study are the NP characteristics and their workforce distribution relative to rural and health professional shortage areas (HPSAs). Data sources:Method: A questionnaire was administered to NPs in 12 Southern states. Other data sources included (a) the Health Resources and Services Administration, which identified HPSAs; and (b) data from the U.S. Census Bureau, to distinguish urban and rural areas. Conclusions:Approximately 72% of NPs worked in HPSAs and less than half of the NPs worked in the rural area. Family NPs were more likely to practice in rural and HPSAs. Employment in primary care was more likely to occur in rural and HPSAs. Racial diversity was almost nonexistent within the NP population. Implication for practice:This research does demonstrate that NPs are practicing in rural and underserved areas as conceived decades ago, but there is still a great demand and gap to fill. To optimize their effectiveness, NPs need to practice to the full extent of their education. Additionally, more research and strategies to help diversify the workforce is needed.

Cross-Cultural Evaluation of Item Wording Effects on an Attitudinal Scale

Previous studies have shown that method effects associated with item wording produce artifactual factors and threaten scale validity. This study examines item wording effects on a scale of attitudes toward learning mathematics for Taiwanese and U.S. samples. Analyses from a series of CFA (confirmatory factor analysis) models support the presence of method effects for both samples. In addition, findings show that U.S. students tended to report higher means on not only the substantive factors but also the method factor, compared to Taiwanese students. The effect sizes on the mean differences are medium to large.

Beyond “Just Saying No”: A Preliminary Evaluation of Strategies College Students Use to Refuse Sexual Activity

Preventing sexual assault is a core goal for universities as prevalence rates of sexual assault remain high, particularly among college students. A key mechanism thought to decrease rates of sexual assault is teaching college students how to give clear, explicit, verbal refusals. However, there is a paucity of research regarding how college students refuse sex. Thus, the purpose of this study was to understand different behavioral strategies college students would use to refuse sex. A sample of 773 heterosexual college students (523 women, 250 men) were recruited from two large southern universities in the USA to complete a survey on sexual communication. Thirty-eight items assessing verbal and behavioral cues that college students would use to refuse vaginal–penile sex were written based on previous, formative research. Items were assessed by the research team through an exploratory factor analyses, followed by a confirmatory factor analysis (CFA). The results yielded a three-factor structure: direct nonverbal refusals, direct verbal refusals, and indirect nonverbal refusals; CFA results suggested a good fit index for the model. Two independent sample t tests were conducted to examine differences in refusal cues across gender and relationship status; significant differences in refusals emerged for both. The three-factor structure depicting refusal cues was similar to previous work depicting cues college students use to communicate sexual consent; such information could inform sexual assault prevention programming.