“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

Social Predictors of Doctoral Student Mental Health and Well-Being

Graduate students\u27 mental health and well-being is a prominent concern across various disciplines. However, early predictors of mental health and well-being in graduate education, specifically doctoral education, have rarely been studied. The present study evaluated both the underlying latent classification of individuals\u27 mental well-being and predictors of those classifications. Results estimated two latent classes of students\u27 mental health and well-being: one class with generally high levels of mental well-being and one with lower levels of mental well-being. Regression analyses showed that mentoring in the second year of doctoral study, certainty of choice in the thrid year, and both academic development and sense of belonging in the fourth year were positive predictors of membership in the higher mental well-being class. In contrast to some prior studies, demographic variables were not related to the identified well-being classifications. Regression analyses further showed that mental well-being was negatively related to participants\u27 number of publications and research self-efficacy, indicating a problematic relationship between scholarly productivity and confidence and well-being. These findings may be used to identify and provide targeted support for students who are at-risk for having or developing lower levels of mental well-being in their graduate programs

Understanding the Transient Nature of STEM Doctoral Students’ Research Self-Efficacy Across Time: Considering the Role of Gender, Race, and First-Generation College Status

Developing research self-efficacy is an important part of doctoral student preparation. Despite the documented importance of research self-efficacy, little is known about the progression of doctoral students’ research self-efficacy over time in general and for students from minoritized groups. This study examined both within- and between-person stability of research self-efficacy from semester to semester over 4 years, focusing on doctoral students in biological sciences (N = 336). Using random intercept autoregressive analyses, we evaluated differences in stability across gender, racially minoritized student status, and first-generation student status. Results showed similar mean levels of self-efficacy across demographic groups and across time. However, there were notable differences in between-person and within-person stability over time, specifically showing higher between-person and lower within-person stability for racially minoritized and first-generation students. These findings indicate that racially minoritized and first-generation students’ research self-efficacy reports were less consistent from semester to semester. Such results may indicate that non-minoritized and continuing-generation students’ experiences from semester to semester typically reinforce their beliefs about their own abilities related to conducting research, while such is not the case for racially minoritized nor first-generation students. Future research should examine what types of experiences impact self-efficacy development across doctoral study to offer more precise insights about factors that influence these differences in within-person stability

Identifying Faculty and Peer Interaction Patterns of First-Year Biology Doctoral Students: A Latent Class Analysis

Faculty and peer interactions play a key role in shaping graduate student socialization. Yet, within the literature on graduate student socialization, researchers have primarily focused on understanding the nature and impact of faculty alone, and much less is known about how peer interactions also contribute to graduate student outcomes. Using a national sample of first-year biology doctoral students, this study reveals distinct categories that classify patterns of faculty and peer interaction. Further, we document inequities such that certain groups (e.g., underrepresented minority students) report constrained types of interactions with faculty and peers. Finally, we connect faculty and peer interaction patterns to student outcomes. Our findings reveal that, while the classification of faculty and peer interactions predicted affective and experiential outcomes (e.g., sense of belonging, satisfaction with academic development), it was not a consistent predictor of more central outcomes of the doctoral socialization process (e.g., research skills, commitment to degree). These and other findings are discussed, focusing on implications for future research, theory, and practice related to graduate training

Feeding Two Birds With One Scone? The Relationship Between Teaching and Research for Graduate Students Across the Disciplines

We surveyed over 300 graduate students at a Southeastern research university to increase our understanding of their perceptions of (a) the connection between teaching and research, (b) the means by which integration occurs, and (c) the extent to which teaching and research contribute to a shared skill set that is of value in both contexts. We also examined differences across disciplines in the perception of this teaching-research nexus. Overall, findings indicate that graduate students perceive important relationships between teaching and research, and they point toward opportunities for administrators to promote teaching and research integration

Numerische Verfahren zur dynamischen Komplexitätsreduktion biochemischer Reaktionssysteme

Zunehmende Größe und Komplexität von kinetischen Modellen biochemischer Systeme erfordern effiziente numerische Methoden zur Identifizierung funktioneller Einheiten, die unabhängig voneinander betrachtet werden können. Darüber hinaus verlangt das hochgradig nichtlineare Verhalten biologischer Systeme dynamische Verfahren zur Komplexitätsreduktion. Im Rahmen dieser Arbeit wurden methodische Ansätze entwickelt, welche die modulare Struktur biochemischer Netzwerke dynamisch analysieren und eine Aussage über die Auswirkungen zeitabhängiger Spezies- bzw. Flussstörungen auf das Verhalten der Systeme ermöglichen. Die lokale Methode zur Komplexitätsreduktion basiert auf dem Konzept der Zeitskalenseparation und erlaubt eine fehlerkontrollierte Analyse von Spezieskopplungen an die maßgebende Dynamik der biochemischen Netzwerke in einer kleinen Umgebung des Referenzpunktes auf der Lösungstrajektorie. Eine Erweiterung des lokalen Ansatzes zur Komplexitätsreduktion stellen die globalisierten Verfahren dar. Sie beruhen auf einer Sensitivitätsanalyse entlang der Lösungstrajektorien, die auf vorher definierten Zeitintervallen stattfindet. Zusätzlich zur stückweisen Analyse der Spezieskopplungen ermöglichen die globalen Verfahren eine fehlerkontrollierte Identifizierung lokaler Erhaltungsbeziehungen. Weiterhin bildet eine modifizierte Hauptkomponentenanalyse der Flusskontrollkoeffizienten, welche die Propagation der Flussstörungen mit der Zeit beschreiben, die Basis eines Algorithmus zur Analyse wechselseitiger Flussbeziehungen in Reaktionssystemen. Die aussagekräftigen Anwendungen der entwickelten Verfahren auf das Peroxidase-Oxidase-Modell und auf unterschiedliche Modelle für Glykolyse in Hefe zeigen die systembiologische Relevanz der Methoden im Sinne von Gewinnung funktioneller Einsichten in die Dynamik biochemischer Systeme

Finding a Fit: Biological Science Doctoral Students’ Selection of a Principal Investigator and Research Laboratory

In the laboratory-based disciplines, selection of a principal investigator (PI) and research laboratory (lab) indelibly shapes doctoral students’ experiences and educational outcomes. Framed by the theoretical concept of person–environment fit from within a socialization model, we use an inductive, qualitative approach to explore how a sample of 42 early-stage doctoral students enrolled in biological sciences programs made decisions about fitting with a PI and within a lab. Results illuminated a complex array of factors that students considered in selecting a PI, including PI relationship, mentoring style, and professional stability. Further, with regard to students’ lab selection, peers and research projects played an important role. Students actively conceptualized trade-offs among various dimensions of fit. Our findings also revealed cases in which students did not secure a position in their first (or second) choice labs and had to consider their potential fit with suboptimal placements (in terms of their initial assessments). Thus, these students weighted different factors of fit against the reality of needing to secure financial support to continue in their doctoral programs. We conclude by presenting and framing implications for students, PIs, and doctoral programs, and recommend providing transparency and candor around the PI and lab selection processes

Cognitive Apprenticeship and the Supervision of Science and Engineering Research Assistants

We explore and critically reflect on the process of science and engineering research assistant skill development both within laboratory-based research teams and, when no team is present, within the faculty supervisor-research assistant interactions. Using a performance-based measure of research skill development, we identify research assistants who, over the course of an academic year of service as a researcher, markedly developed, modestly developed, or failed to develop their research skills. Interviews with these research assistants and their faculty supervisors, seen through the lens of cognitive apprenticeship, provide insight into this variation. We found that within the contours of supervisory relationships and research teams, research skill development is indelibly shaped, for better or worse, by supervisor influence and abundant trial-and-error