Lectures

In alphabetical order by speaker

Adriene Beltz, University of Michigan

The Psychological Correlates of Hormonal Contraceptive Use: General Trends and Individual Differences from Puberty to Menopause

Worldwide, four hundred million women and people with uteri use hormonal contraceptives (HCs), yet surprisingly little is known about the cognitive and mental health correlates of “the pill.” This is a crucial knowledge gap, especially at a moment when reproductive health options are narrowing in the United States and are under scrutiny around the globe. Thus, the goal of this talk is to describe how exogenous ovarian hormone influences on behavior can be studied in HC users, and to provocatively synthesize the extant literature regarding the impact of HCs on spatial cognition, verbal memory, depression, and anxiety. Special consideration will be given to potential lifespan effects, individual differences in effects across women and people with uteri, and research methodology. The talk will end by sharing new advances and future directions for developmental research.

  • Beltz, A. M. (2022). Hormonal contraceptive influences on cognition and psychopathology: Past methods, present inferences, and future directions. Frontiers in Neuroendocrinology. Advance online publication. https://doi.org/10.1016/j.yfrne.2022.101037

 

Steven M. Boker, University of Virginia

Products of Variables in Structural Equation Models

A general method is introduced in which variables that are products of other variables in the context of a structural equation model (SEM) can be decomposed into the sources of variance due to the multiplicands.  The result is a new category of SEM which we call a Products of Variables Model (PoV).  Some useful and practical features of PoV models include estimation of interactions between latent variables, latent variable moderators, manifest moderators with missing values, and manifest or latent squared terms.  Expected means and covariances are analytically derived for a simple product of two variables and it is shown that the method reproduces previously published results for this special case.  It is shown algebraically that using centered multiplicands results in an unidentified model, but if the multiplicands have non-zero means, the result is identified.  The method has been implemented in OpenMx and Onyx and is applied in five extensive simulations.  An exciting new use for PoV is the prospect of estimating parameters in nonlinear dynamical systems.

  • Boker, S., von Oertzen, T., Pritikin, J., Hunter, M. D., Brick, T., Brandmaier, A., & Neale, M. (2022). Products of variables in structural equation models. Unpublished manuscript.
  • Boker, S., & von Oertzen, T. (2022). Derivation of the expected covariance matrix and means vector of Z = bXY + e using products of variables. Unpublished manuscript.

 

Martin Brunner, Universität Potsdam

A New Type of Evidence Synthesis: Meta-analyzing Individual Participant Data From Educational Large-scale Assessments

Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational large-scale assessments (ELSAs) or social, health, and economic survey and panel studies. The meta-analytic integration of these results offers unique and novel research opportunities to provide strong empirical evidence of the consistency and generalizability of important phenomena and trends. Using ELSAs as an example, I illustrate how to use the two-stage approach to IPD meta-analysis to account for the statistical challenges of complex survey designs (e.g., sampling weights, clustered and missing IPD), first, to conduct descriptive analyses (Stage 1), and second, to integrate results with three-level meta-analytic and meta-regression models to take into account dependencies among effect sizes (Stage 2). Because complex social, health, or economic survey and panel studies share many methodological features with ELSAs, the two-stage approach to IPD meta-analyses is also helpful for synthesizing research evidence from these studies.

  • Brunner, M., Keller, L., Stallasch, S. E., Kretschmann, J., Hasl, A., Preckel, F., Lüdtke, O., & Hedges, L. V. (2022). Meta-analyzing individual participant data from studies with complex survey designs: a tutorial on using the two-stage approach for data from educational large-scale assessments. Research Synthesis Methods. Advance online publication. https://doi.org/10.1002/jrsm.1584

 

Kai Schnabel Cortina, University of Michigan

Can a Metaphor Be Racist? The Concept of Classroom Climate and Its Common Operationalization Seen Through a Critical Lens
The current study interrogates the predominant conceptualization and operationalization of classroom climate. Researchers tend to average questionnaire ratings of all students in a class. We argue that this is problematic as it runs the risk of silencing minority students whose experience may be different from majority students in the same classroom. In a secondary data analysis based on data from the National Center for Teacher Effectiveness (N = 1,842 students in 101 classrooms), we found that minoritized students often disagree in their assessments of classroom climate with White students – in either direction. We concluded that using a consensus construct when there is no consensus obfuscates important and informative group differences.
 
  • Pianta, R. C., & Hamre, B. K. (2009). Conceptualization, measurement, and improvement of classroom processes: Standardized observation can leverage capacity. Educational Researcher, 38(2), 109–119. https://doi.org/10.3102/0013189X09332374
  • Wang, M.-T., & Degol, J. L. (2016). School climate: A review of the construct, measurement, and impact on student outcomes. Educational Psychology Review, 28(2), 315–352. https://doi.org/10.1007/s10648-015-9319-1
 
Charles C. Driver, University of Zurich
Linking Theory and Statistical Models of Processes in Time
Multivariate longitudinal models, such as the cross-lagged panel and latent change score models, offer hopes of deep insight into the relations between constructs. All too often however, such models are misunderstood and misapplied, with sometimes fantastical causal conclusions resulting. I will discuss the use of such models as representations of theory, some traps and partial solutions for causal interpretation, as well as what we can learn from such modelling approaches even when we accept the models are imperfect.
 
  • Driver, C. C. (2022, January 14). Inference with cross-lagged effects: Problems in time and new interpretations. OSF Preprints. https://doi.org/10.31219/osf.io/xdf72
  • Driver, C. C. & Tomasik M. J. (2022). Formalizing complex developmental phenomena as continuous-time systems: Learning gains in multiple domains. Unpublished manuscript.
 
Alexandra M. Freund, University of Zurich
The Bucket List Effect
The central argument of this talk is that historical changes in longevity in Western societies and the weakening of social expectations regarding the timing of developmental goals lead to a compression of the time for pursuing highly demanding developmental goals related to work and family in middle adulthood. The expectation of longevity might lead to the construction of a “bucket list”, postponing important leisure and social goals to the post-retirement phase. Jointly, the weakening of age-related social expectations and the expectation of a long post-retirement phase might result in a stronger segregation of the life course: Education in “emerging adulthood,” work and family in later young and middle adulthood, leisure and social goals in later adulthood. This segregation also conforms to a cultural script following the protestant work-ethic of delaying gratification by pursuing obligatory goals first (work, family) and only then turn to “play” after retirement (leisure, social goals). The segmentation of the life course has implications for self-regulatory demands, such that the importance of goal selection increases in young adulthood, the importance of managing multiple goals in middle adulthood, and the importance of self-regulation for the pursuit of ill-defined goals in old age. Taken together, historical changes in the increased life expectancy in Western countries and weakened age-related expectations represent a challenge and an opportunity for developmental regulation across adulthood.
 
  • Freund, A. M., Nikitin, J., & Ritter, J. O. (2009). Psychological consequences of longevity: The increasing importance of self-regulation in old age. Human Development, 52(1), 1–37. https://www.jstor.org/stable/26764887
 
Aaron Peikert, MPI for Human Development
Reproducible Research in R: A Talk on How to Do the Same Thing More Than Once
Reproducibility has long been considered integral to the scientific method. An analysis is considered reproducible if an independent person can obtain the same results from the same data. Until recently, detailed descriptions of methods and analyses were the primary instrument for ensuring scientific reproducibility. Technological advancements now 
enable scientists to achieve a more comprehensive standard that allows anyone to access a digital research repository and reproduce all computational steps from raw data to final report, including all relevant statistical analyses, with a single command. This method has far-reaching implications for scientific archiving, reproducibility and replication, scientific productivity, and the credibility and reliability of scientific knowledge.
 
  • Peikert, A., & Brandmaier, A. M. (2021). A reproducible data analysis workflow with R Markdown, Git, Make, and Docker. Quantitative and Computational Methods in Behavioral Sciences, 1, Article e3763. https://doi.org/10.5964/qcmb.3763
  • van Lissa, C. J., Brandmaier, A. M., Brinkman, L., Lamprecht, A.-L., Peikert, A., Struiksma, M. E., & Vreede, B. M. I. (2021). WORCS: A workflow for open reproducible code in science. Data Science, 4(1), 29–49. https://doi.org/10.3233/DS-210031

 

Laurel Raffington, MPI for Human Development
Pushing Biomarkers Beyond Biological Reductionism: A Story of DNA-Methylation Measures of Aging Across the Lifespan

In 1997, Taylor and Repetti posed the question “What is an unhealthy environment and how does it get under the skin?” Since then, a surge of research has associated environmental, health, and behavioral measures with advancingly complex biological markers measured “under the skin”, including brain, blood, protein, microbiome, transcription, and genome-level markers. Critics of this work highlight the risk of biological reductionism and determinism. Proponents argue that a biosocial perspective that situates biological measures in transactional models of human development can help us understand how experience becomes biology, and how biology becomes experience. In this session I would like to think with you about how we may be able to push biomarker research beyond decontextualized and reductionist approaches. I will present recent findings with DNA-methylation measures of biological aging as an example of how biological markers can become tools to advance our understanding of developmental processes across the human lifespan.

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