These will include talks that I've given at conferences or other gatherings.

Make Power Fun (Again?)

Make Power Fun (Again?) Brandon LeBeau University of Iowa Overview (G)LMMs Power simglm package Shiny Demo - Broken! Linear Mixed Model (LMM) Power Power is the ability to statistically detect a true effect (i.e. non-zero population effect). For simple models (e.g. t-tests, regression) there are closed form equations for generating power. R has routines for these: power.t.test, power.anova.test Gpower3 Power Example n <- seq(4, 1000, 2) power <- sapply(seq_along(n), function(i) power.

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Extending accessibility of open-source statistical software to the masses A shiny case study

Extending accessibility of open-source statistical software to the masses: A shiny case study Brandon LeBeau University of Iowa R R is an open source statistical programming language. Pros: Common statistical procedures are found in R Can extend functionality with packages/functions Cons: Need to be comfortable with code Flexibility of R R is powerful and flexible due to the many user written packages.

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Estimating NCAA Football Coaches’ Abilities An Application of Item Response Theory

Estimating NCAA Football Coaches’ Abilities An Application of Item Response Theory Brandon LeBeau, Andrew Zieffler, and Kyle Nickodem University of Iowa & University of Minnesota Background Began after Tim Brewster was fired at the University of Minnesota. Now they have a new coach again! Wanted to try to predict next great coach. Proceeded to explore data available to answer this question. Data Data came from a few sources: http://www.

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