“How Well Does Your Structural Equation Model Fit Your Data?”: Is Marcoulides and Yuan’s Equivalence Test the Answer?

Structural equation modeling is an ideal data analytical tool for testing complex relationships among many analytical variables. It can simultaneously test multiple mediating and moderating relationships, estimate latent variables on the basis of related measures, and address practical issues such as nonnormality and missing data. To test the extent to which a hypothesized model provides an appropriate characterization of the collective relationships among its variables, researchers must assess the “fit” between the model and the sample’s data. However, interpreting estimates of model fit is a problematic process. The traditional inferential test of model fit, the chi-square test, is biased due to sample size. Fit indices provide descriptive (i.e., noninferential) values of model fit (e.g., comparative fit index, root-mean-square error of approximation), but are unable to provide a definitive “acceptable” or “unacceptable” fit determination. Marcoulides and Yuan have introduced an equivalence-testing technique for assessing model fit that combines traditional descriptive fit indices with an inferential testing strategy in the form of confidence intervals to facilitate more definitive fit conclusions. In this paper, we explain this technique and demonstrate its application, highlighting the substantial advantages it offers the life sciences education community for drawing robust conclusions from structural equation models. A structural equation model and data set (N = 1902) drawn from previously published research are used to illustrate how to perform and interpret an equivalence test of model fit using Marcoulides and Yuan’s approach

Self-Efficacy Change Associated with a Cognitive Load-Based Intervention in an Undergraduate Biology Course

Cognitive load theory (CLT) holds that discovery learning and other instructional strategies imposing high levels of extraneous load on novice learners hinder learning. Such learning conditions are also associated with significant drops in persistence, a key measure of motivation. However, research within the CLT framework typically engages motivation as a necessary precursor to learning, rather than as an outcome of instruction. In this study, we examine changes in motivational beliefs as outcomes of learners\u27 cognitive processes through a CLT lens as they engage with instruction. Using a double-blind quasi-experimental design, we manipulate the level of cognitive load imposed on participants through instruction and assess changes in self-efficacy from pre-to post-intervention. In an analysis of data from students enrolled in an undergraduate biology course (n = 2078), students in the treatment condition demonstrated significantly higher performance on end-of-semester lab reports and self-efficacy measures. However, post-instruction self-efficacy was not significantly related to performance, controlling for pre-instruction self-efficacy, gender, and scientific reasoning ability. These findings introduce the possibility that the cognitive load imposed on working memory during instruction may affect motivational beliefs and provides a foundation to further explore connections between historically distinct theoretical frameworks such as CLT and social cognitive theory

Time-to-Credit Gender Inequities of First-Year PhD Students in the Biological Sciences

Equitable gender representation is an important aspect of scientific workforce development to secure a sufficient number of individuals and a diversity of perspectives. Biology is the most gender equitable of all scientific fields by the marker of degree attainment, with 52.5% of PhDs awarded to women. However, equitable rates of degree completion do not translate into equitable attainment of faculty or postdoctoral positions, suggesting continued existence of gender inequalities. In a national cohort of 336 first-year PhD students in the biological sciences (i.e., microbiology, cellular biology, molecular biology, develop-mental biology, and genetics) from 53 research institutions, female participants logged significantly more research hours than males and were significantly more likely than males to attribute their work hours to the demands of their assigned projects over the course of the academic year. Despite this, males were 15% more likely to be listed as authors on published journal articles, indicating inequality in the ratio of time to credit. Given the cumulative advantage that accrues for students who publish early in their graduate careers and the central role that scholarly productivity plays in academic hiring decisions, these findings collectively point to a major potential source of persisting underrepresentation of women on university faculties in these fields

Longitudinal trends in food cravings following Roux-en-Y gastric bypass in an adolescent sample

This is the author's accepted manuscript. Made available by the permission of the publisher.Background Food cravings are more prevalent and potentially problematic for many individuals with obesity. Initial evidence suggests that bariatric surgery has some short-term beneficial effects on cravings in adults, but little is known about the effect on adolescents or the trajectory beyond 6 months. Methods The purpose of the present study was to determine the longitudinal effect of Roux-en-Y gastric bypass (RYGB) on food cravings in a sample of adolescents with severe obesity (body mass index (BMI) ≥40 kg/m2). Sixteen adolescents were recruited and underwent RYGB. Participants completed the Food Craving Inventory before RYGB, and 3, 6, 12, 18, and 24 months postoperatively. The present study took place in a single pediatric tertiary care hospital. Results RYGB produced a negative (cravings decreased as time increased) nonlinear trend for total food cravings as well as for each individual subscale (sweets, high fat foods, carbohydrates, fast food) over the 24-month study period. This means that while cravings decrease postsurgically, there is a decline in the slope with the line reaching asymptote at approximately 18 months. BMI change was not a significant predictor of food cravings, but low statistical power may account for this lack of significance. Conclusion These findings provide preliminary evidence that RYGB decreases food cravings in adolescents

Graduate students\u27 teaching experiences improve their methodological research skills

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

A longitudinal study of several potential mediators of the relationship between child maltreatment and posttraumatic stress disorder symptoms

Child maltreatment is a reliable predictor of post-traumatic stress disorder (PTSD) symptoms. However, not all maltreated children develop PTSD symptoms, suggesting that additional mediating variables explain how certain maltreated children develop PTSD symptoms when others do not. The current study tested three potential mediators of the relationship between child maltreatment and subsequent PTSD symptoms: 1) respiratory sinus arrhythmia reactivity, 2) cortisol reactivity, and 3) experiential avoidance, or the unwillingness to experience painful private events such as thoughts and memories. Maltreated (n = 51) and non-maltreated groups (n = 59) completed a stressor paradigm, a measure of experiential avoidance, and a semi-structured interview of PTSD symptoms. One year later, participants were re-administered the PTSD symptoms interview. Results of a multiple mediator model showed the set of potential mediators mediated the relationship between child maltreatment and subsequent PTSD symptoms. However, experiential avoidance was the only significant specific indirect effect, demonstrating that maltreated children avoiding painful private events after the abuse were more likely to develop a range of PTSD symptoms one year later. These results highlight the importance of experiential avoidance in the development of PTSD symptoms for maltreated children and implications for secondary prevention and clinical intervention models are discussed

The effectiveness of a low-intensity problem-solving intervention for common adolescent mental health problems in New Delhi, India: protocol for a school-based, individually randomized controlled trial with an embedded stepped-wedge cluster randomized controlled recruitment trial

Background Conduct, anxiety and depressive disorders account for over 75% of the adolescent mental health burden globally. The current protocol will test a low-intensity problem-solving intervention for school-going adolescents with common mental health problems in India. The protocol also tests the effects of a classroom-based sensitization intervention on the demand for counselling services in an embedded recruitment trial. Methods We will conduct a two-arm individually randomized controlled trial in six Government-run secondary schools in New Delhi. The targeted sample is 240 adolescents in grades 9-12 with persistent, elevated mental health symptoms and associated impact. Participants will receive either a brief problem-solving intervention delivered over 3 weeks by lay counsellors (intervention), or enhanced usual care comprised of problem-solving booklets (control). Self-reported adolescent mental health symptoms and idiographic problems will be assessed at 6 weeks (co-primary outcomes) and again at 12 weeks post-randomization. In addition, adolescent-reported impact of mental health difficulties, perceived stress, mental wellbeing and clinical remission, as well as parent-reported adolescent mental health symptoms and impact scores, will be assessed at 6 and 12 weeks post-randomization. We will also complete a parallel process evaluation, including estimations of the costs of delivering the interventions. An embedded recruitment trial will apply a stepped-wedge, cluster (class)-randomized controlled design in 70 classes across the six schools. This will evaluate the added impact of a classroom-based sensitization intervention over school-level recruitment sensitization activities on the primary outcome of referral rate into the host trial (i.e. the proportion of adolescents referred as a function of the total sampling frame in each condition of the embedded recruitment trial). Other outcomes will be the proportion of referrals eligible to participate in the host trial, proportion of self-generated referrals, and severity and pattern of symptoms among referred adolescents in each condition. Power calculations were undertaken separately for each trial. A detailed statistical analysis plan will be developed separately for each trial prior to unblinding. Discussion Both trials were initiated on 20 August 2018. A single research protocol for both trials offers a resource-efficient methodology for testing the effectiveness of linked procedures to enhance uptake and outcomes of a school-based psychological intervention for common adolescent mental health problems

Specification searches in multilevel structural equation modeling: A Monte Carlo investigation

Sample data obtained via cluster sampling rather than simple random sampling requires the use of specialized multilevel statistical analysis techniques, such as multilevel structural equation modeling, to model within-cluster and between-cluster variation appropriately. Properly modeling both within-cluster and between-cluster variation could be of substantive interest in numerous applied research settings. However, applied researchers typically test only a within-cluster (i.e., individual difference) theory; specifying a between-cluster model in the absence of theory involves a specification search. Consistent with previous specification search studies, this dissertation manipulated the following independent variables: starting model, search method, and method of Type-I error control as independent variables. Further, consistent with previous multilevel research studies, this dissertation also manipulated the number of clusters, cluster sample size, and intraclass correlation magnitude as independent variables. The main dependent variable of interest was which combination of start model, search type, and method of Type-I error control best recovered the population between-cluster model. Additional dependent variables were also examined to assess the precision of specification search efforts. Results showed that a saturated start model, univariate specification search, and no Type-I error control best recovered the population between-cluster model. However, this specification search method recovered the population model in less than one in five attempts at the largest sample size. A majority of the specification searches recovered the population model in less than five percent of all attempts, and the remaining specification search efforts failed to recover the population model under any conditions. Overall, specification search efforts were more likely to produce a notably misspecified model with biased parameter estimates, an under-identified model, or an inadmissible solution. Model complexity, non-normally distributed data, and within-cluster model misspecification were not manipulated as independent variables in this dissertation. Further, the current results were based on a multilevel path model that may or may not generalize to other multilevel designs, such as confirmatory factor analyses and full structural equation models. Model complexity, non-normally distributed data, within-cluster model misspecification, and advanced analysis designs could be incorporated in future multilevel specification search studies by adapting the models used in previous non-multilevel specification search investigations