James Peugh

Missing Data in Educational Research: A Review of Reporting Practices and Suggestions for Improvement

Missing data analyses have received considerable recent attention in the methodological literature, and two “modern” methods, multiple imputation and maximum likelihood estimation, are recommended. The goals of this article are to (a) provide an overview of missing-data theory, maximum likelihood estimation, and multiple imputation; (b) conduct a methodological review of missing-data reporting practices in 23 applied research journals; and (c) provide a demonstration of multiple imputation and maximum likelihood estimation using the Longitudinal Study of American Youth data. The results indicated that explicit discussions of missing data increased substantially between 1999 and 2003, but the use of maximum likelihood estimation or multiple imputation was rare; the studies relied almost exclusively on listwise and pairwise deletion.

A Practical Guide to Multilevel Modeling.

Collecting data from students within classrooms or schools, and collecting data from students on multiple occasions over time, are two common sampling methods used in educational research that often require multilevel modeling (MLM) data analysis techniques to avoid Type-1 errors. The purpose of this article is to clarify the seven major steps involved in a multilevel analysis: (1) clarifying the research question, (2) choosing the appropriate parameter estimator, (3) assessing the need for MLM, (4) building the level-1 model, (5) building the level-2 model, (6) multilevel effect size reporting, and (7) likelihood ratio model testing. The seven steps are illustrated with both a cross-sectional and a longitudinal MLM example from the National Educational Longitudinal Study (NELS) dataset. The goal of this article is to assist applied researchers in conducting and interpreting multilevel analyses and to offer recommendations to guide the reporting of MLM analysis results.

Using the SPSS Mixed Procedure to Fit Cross-Sectional and Longitudinal Multilevel Models

Beginning with Version 11, SPSS implemented the MIXED procedure, which is capable of performing many common hierarchical linear model analyses. The purpose of this article was to provide a tutorial for performing cross-sectional and longitudinal analyses using this popular software platform. In doing so, the authors borrowed heavily from Singer’s overview of SAS PROC MIXED, duplicating her analyses using the SPSS MIXED procedure.

Graduate Students’ Teaching Experiences Improve Their Methodological Research Skills

Teaching is not wasted time. Science, technology, engineering, and mathematics (STEM) graduate students are often encouraged to maximize their engagement with supervised research and minimize teaching obligations. However, the process of teaching students engaged in inquiry provides practice in the application of important research skills. Using a performance rubric, we compared the quality of methodological skills demonstrated in written research proposals for two groups of early career graduate students (those with both teaching and research responsibilities and those with only research responsibilities) at the beginning and end of an academic year. After statistically controlling for preexisting differences between groups, students who both taught and conducted research demonstrate significantly greater improvement in their abilities to generate testable hypotheses and design valid experiments. These results indicate that teaching experience can contribute substantially to the improvement of essential research skills.

Using an EM Covariance Matrix to Estimate Structural Equation Models with Missing Data: Choosing an Adjusted Sample Size to Improve the Accuracy of Inferences.

Two methods, direct maximum likelihood (ML) and the expectation maximization (EM) algorithm, can be used to obtain ML parameter estimates for structural equation models with missing data (MD). Although the 2 methods frequently produce identical parameter estimates, it may be easier to satisfy missing at random assumptions using EM. However, no single value of N is applicable to the EM covariance matrix, and this may compromise inferences gained from the model fit statistic and parameter standard errors. The purpose of this study was to identify a value of N that provides accurate inferences when using EM. If all confirmatory factor analysis model indicators have MD, results suggest that the minimum N per covariance term yields honest Type 1 error rates. If MD are restricted to a subset of indicators, the minimum N per variance works well. With respect to standard errors, the harmonic mean N per variance term produces honest confidence interval coverage rates.

What About Men? Social Comparison and the Effects of Media Images on Body and Self-Esteem

Research has consistently shown that exposure to ideal female images negatively influences womens self-evaluations (e.g., Brown, Novick, Lord, & Richards, 1992; Henderson-King, Henderson-King, & Hoffman, 2001). However, minimal research has examined the effects of media-portrayed male images on men

Changes in Pain Coping, Catastrophizing, and Coping Efficacy After Cognitive-Behavioral Therapy in Children and Adolescents With Juvenile Fibromyalgia

UNLABELLED A recent randomized multisite clinical trial found that cognitive-behavioral therapy (CBT) was significantly more effective than fibromyalgia education (FE) in reducing functional disability in adolescents with juvenile fibromyalgia (JFM). The primary objective of this study was to examine the psychological processes of CBT effectiveness by evaluating changes in pain coping, catastrophizing, and coping efficacy and to test these changes as mediators of continued improvements in functional disability and depressive symptoms at 6-month follow-up. One hundred adolescents (11-18 years old) with JFM completed the clinical trial. Coping, catastrophizing, and coping efficacy (Pain Coping Questionnaire) and the outcomes of functional disability (Functional Disability Inventory) and depressive symptoms (Childrens Depression Inventory) were measured at baseline, posttreatment, and 6-month follow-up. Participants in both conditions showed significant improvement in coping, catastrophizing, and efficacy by the end of the study, but significantly greater improvements were found immediately following treatment for those who received CBT. Treatment gains were maintained at follow-up. Baseline to posttreatment changes in coping, catastrophizing, and efficacy were not found to mediate improvements in functional disability or depressive symptoms from posttreatment to follow-up. Future directions for understanding mechanisms of CBT effectiveness in adolescents with chronic pain are discussed. PERSPECTIVE CBT led to significant improvements in pain coping, catastrophizing, and efficacy that were sustained over time in adolescents with juvenile fibromyalgia. Clinicians treating adolescents with JFM should focus on teaching a variety of adaptive coping strategies to help patients simultaneously regain functioning and improve mood.

Child Maltreatment History among Newlywed Couples: A Longitudinal Study of Marital Outcomes and Mediating Pathways.

Participants included 202 newlywed couples who reported retrospectively about child maltreatment experiences (sexual abuse, physical abuse, psychological abuse, and neglect) and whose marital functioning was assessed 3 times over a 2-year period. Decreased marital satisfaction at T1 was predicted by childhood physical abuse, psychological abuse, and neglect for husbands; only neglect predicted lower satisfaction for wives. Increased maltreatment of various types was also related to T1 difficulties with marital trust and partner aggression. Dyadic growth curve analyses showed that the marital difficulties reported at T1 tended to remain over the course of the study. Further, in several instances, maltreatment exerted an increasingly detrimental influence on marital functioning over time, particularly for husbands. Examination of possible mediators between maltreatment and reductions in marital satisfaction revealed pathways through decreased sexual activity, increased psychological aggression, and increased trauma symptoms reported by husbands. These findings suggest that clinicians should consider how an adults history of child maltreatment may contribute to current marital dysfunction. The authors also identify possible targets for intervention when working with this population.

Long-Term Outcomes of Adolescents With Juvenile-Onset Fibromyalgia in Early Adulthood

OBJECTIVE: This prospective longitudinal study examined the long-term physical and psychosocial outcomes of adolescents with juvenile-onset fibromyalgia (JFM), compared with healthy control subjects, into early adulthood. METHODS: Adolescent patients with JFM initially seen at a pediatric rheumatology clinic (n = 94) and age- and gender-matched healthy control subjects (n = 33) completed online measures of demographic characteristics, pain, physical functioning, mood symptoms, and health care utilization at ∼6 years’ follow-up (mean age: 21 years). A standard in-person tender-point examination was conducted. RESULTS: Patients with JFM had significantly higher pain (P < .001), poorer physical function (P < .001), greater anxiety (P < .001) and depressive symptoms (P < .001), and more medical visits (P < .001)than control subjects. The majority (>80%) of JFM patients continued to experience fibromyalgia symptoms into early adulthood, and 51.1% of the JFM sample met American College of Rheumatology criteria for adult fibromyalgia at follow-up. Patients with JFM were more likely than control subjects to be married and less likely to obtain a college education. CONCLUSIONS: Adolescent patients with JFM have a high likelihood of continued fibromyalgia symptoms into young adulthood. Those who met criteria for fibromyalgia in adulthood exhibited the highest levels of physical and emotional impairment. Emerging differences in educational attainment and marital status were also found in the JFM group. JFM is likely to be a long-term condition for many patients, and this study for the first time describes the wide-ranging impact of JFM on a variety of physical and psychosocial outcomes that seem to diverge from their same-age peers.

Modeling Unobserved Heterogeneity Using Latent Profile Analysis: A Monte Carlo Simulation

Latent profile analysis (LPA) has become a popular statistical method for modeling unobserved population heterogeneity in cross-sectionally sampled data, but very few empirical studies have examined the question of how well enumeration indexes accurately identify the correct number of latent profiles present. This Monte Carlo simulation study examined the ability of several classes of enumeration indexes to correctly identify the number of latent population profiles present under 3 different research design conditions: sample size, the number of observed variables used for LPA, and the separation distance among the latent profiles measured in Mahalanobis D units. Results showed that, for the homogeneous population (i.e., the population has k = 1 latent profile) conditions, many of the enumeration indexes used in LPA were able to correctly identify the single latent profile if variances and covariances were freely estimated. However, for a heterogeneous population (i.e., the population has k = 3 distinct latent profiles), the correct identification rate for the enumeration indexes in the k = 3 latent profile conditions was typically very low. These results are compared with the previous cross-sectional mixture modeling studies, and the limitations of this study, as well as future cross-sectional mixture modeling and enumeration index research possibilities, are discussed.