Simulation and Power Analysis of Generalized Linear Mixed Models

Simulation and Power Analysis of Generalized Linear Mixed Models Brandon LeBeau University of Iowa Overview Power simglm package Shiny Demo 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(20, 1000, 5) power <- sapply(seq_along(n), function(i) power.

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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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Simulation and power analysis of generalized linear mixed models

Simulation and power analysis of generalized linear mixed models Brandon LeBeau University of Iowa Overview (G)LMMs Power simglm package Demo Shiny App! 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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