News and Updates
We are pleased to make available a number of materials related to a workshop titled Introduction to Growth Curve Modeling: An Overview and Recommendations for Practice that Curran-Bauer Analytics conducted at the biennial convention of the Society for Research on Adolescence on April 3rd, 2016. We have posted a copy of the slides from the workshop as well as example data and syntax files for fitting mulitilevel growth models in SAS, SPSS, and Stata and latent curve models in Stata and Mplus. We hope these resources will be of use to those who are beginning to consider the use of growth models in their own research.Read More
On March 23, North Carolina Governor McCrory signed into law House Bill 2 (HB2) that bars transgender people from using bathrooms and changing rooms that do not correspond to the gender stated on their birth certificates. HB2 also explicitly prohibits local municipalities from enacting their own antidiscrimination policies and instead establishes a statewide policy that excludes gay and transgender citizens.
As citizens of North Carolina, we are appalled at the passage of HB2. At Curran-Bauer Analytics, we are deeply committed to fostering a diverse, open, and welcoming community of scientists and scholars and we value and respect each and every individual with whom we work. We are contributing our voice to the rapidly increasing national opposition to HB2 and it is our sincere hope that this unfair and unjust law will quickly be overturned.
Dan Bauer and Patrick CurranRead More
A common challenge when modeling repeated measures data is finding the linear or nonlinear shape that best characterizes the observed pattern of change over time. The SEM-based latent curve model offers several options for modeling nonlinearity, and a particularly flexible method is to freely estimate a subset of factor loadings to define a “latent basis curve”. Although commonly used in practice, there are very important proportionality assumptions that must be met for proper interpretation of the means and variances of the latent basis factors. A recent paper by Wu and Lang (2016) clearly demonstrates that when the proportionality assumption is violated the latent basis model will force the individual trajectories to conform to the assumption and this in turn biases the model estimates. The authors recommend a strategy in which multiple alternative nonlinear functions are evaluated in addition to the latent basis models so that the optimal functional form can be identified for a given sample of data.
Wu, W., & Lang, K. M. (2016). Proportionality Assumption in Latent Basis Curve Models: A Cautionary Note. Structural Equation Modeling: A Multidisciplinary Journal, 23, 140-154.Read More
We’re often asked if there are resources that offer brief introductions to various methodological techniques that can help determine if a particular methodology might be of use in a given research application. One excellent source of introductory workshops is available through the Annual Convention for the Association for Psychological Science (APS). The 2016 APS convention will be held May 26-29 in Chicago and is offering a host of high-quality introductory workshops in a variety of methodological topics taught by many leaders in the field of methodology. Topics include introduction to R, dyadic data analysis, improving reproducibility, methodological approaches to designing adaptive interventions, Bayesian hypothesis testing, and the theory and practice of machine learning, among many others. Most workshops range between two and four hours and offer initial exposure to a number of important quantitative topics in the social and behavioral sciences.Read More
Patrick and Dan bring the same level of dedication in teaching to their workshops at Curran-Bauer Analytics, training a broad audience of researchers in the application of advanced quantitative methodology.Read More