Research Problem IRT models specified as linear mixed models are not new (e.g., Adams, Wilson, & Wu, 1997; Kamata, 2001; Mellenbergh, 1994; Rijmen et al., 2003). Some have discussed evaluating DIF in these frameworks too (e.g., Noorgate and De Boeck, 2005). To our knowledge, these methods have not been explored to which the extent they properly link scores. Heterotypic Continuity We approach this research primarily from a psychological measurement lens, where heterotypic continuity is often of concern ..read more

Intro Stats Assumptions All Math All hand calculations Not Reality What I want Data based, Applied Include code Difficulties Differing levels of computer literacy Unfamiliar with code Enter IDAS What is it? Cloud or server based computational environment for statistics/data science Interact with computational environment in a browser Embeds code with text Jupyter Lab / Notebooks Can run different kernels: R, Python, Julia RStudio Server Full R IDE Benefits - No Setup Benefits - Interesting Data Benefits - Getting back to applied stats Short Demo if time Notebook from my class Open materials he ..read more

As of writing this (June 2022), there is a relatively new version of R, R 4.2.0, published in April of 2022. I like to use recent versions of R, both on my computers, but also on the high performance computing (HPC) system that I use occasionally here at the University of Iowa. Unfortunately, to use up to date versions of R requires a bit of work as the release cycle for R tends to be quicker than the HPC update cycle ..read more

Tidy Meta-Analytic Data Brandon LeBeau & Ariel M. Aloe University of Iowa Rationale Data entry is an important component for quantitative studies Often neglected in courses Messy data can make data manipulation much more difficult Substantial time could be lost due to poor data entry procedures Strong data entry procedures are particularly important in evidence synthesis Rationale 2 Data Organization in Spreadsheets - Broman and Woo (2018), The American Statistician, https://doi ..read more

..read more

Introduction to Statistical Methods (PSQF 4143). Primarily an undergraduate course. Open materials posted here to GitHub course repo. Intermediate Statistical Methods (PSQF 6243). Graduate course. Open materials posted to GitHub course repo, plus course website Computer Packages for Statistical Analysis (PSQF 6250). Graduate course. Open materials on course website ..read more

My first statistical software package I used as an undergrad was SPSS. I was fortunate during my senior year at Luther College to be initially introduced to R. I did not realize it at the time (except for the pretty graphics) that this was the start of something big for me. Fast forward a year to graduate school at the University of Minnesota and the majority of my program was again using SPSS ..read more

This past August I took an opportunity to step back into the University academic world as a Visiting Assistant Professor at the University of Arkansas. I have enjoyed the transition back into the academic world, including a more flexible schedule, variation in topics/duties, and collaborating with colleagues. However, there has been some growing pains, especially regarding creating my own slides for the courses I teach. Although I am using the same books/curriculum used in previous semesters, I am making my own slides and adding my own pieces as I see fit ..read more

Evolution of Statistical Software and Quantitative Methods Brandon LeBeau & Ariel M. Aloe University of Iowa Rationale Extension of work done by Robert Muenchen (http://r4stats.com/articles/popularity/). Focus is on statistical software Addition of quantitative methods Particularly interested in the interaction. Questions of Interest: Exploring which software is popular in published research. How many empirical analyses cite software? Any patterns in software use with quantitative methods? Methods Research synthesis methods were used Web of Knowledge was used to pull in citations for 12 so ..read more

Measuring Psychological Constructs over a Developmental Span: Methodological Approaches Brandon LeBeau University of Iowa Background Petersen, I. T., Lindhiem, O., LeBeau, B., Bates, J. E., Pettit, G. S., Lansford, J. E., & Dodge, K. A. (2018). Development of internalizing problems from adolescence to emerging adulthood: Accounting for heterotypic continuity with vertical scaling. Developmental psychology, 54(3), 586. Peterson, I.T. & LeBeau, B. (In Press). Language Ability in the Development of Externalizing Behavior Problems in Childhood ..read more