SIMR: an R package for power analysis of generalized linear mixed models by simulation

By Peter Green, Catriona J. MacLeod. 2016

1,974 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/330b216f17fc3b9b7d46580bb82cc012886e854a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Michaël A. Stevens
2. Levi Kumle
3. Marc Brysbaert
4. Melissa Le-Hoa Vo
5. Dejan Draschkow
6. Emmanuel Keuleers
7. Saif M. Mohammad
8. Paweł Mandera

In Economics and Econometrics

1. Levi Kumle
2. Melissa Le-Hoa Vo
3. Dejan Draschkow

In Statistics and Probability

1. Michaël A. Stevens
2. Levi Kumle
3. Marc Brysbaert
4. Melissa Le-Hoa Vo
5. Dejan Draschkow

Citations in the corpus

• Power Analysis and Effect Size in Mixed Effects Models: A Tutorial (2018, background): “A particularly interesting R package is simR (Green & MacLeod, 2016; Green, MacLeod, & Alday, 2016).2 2 The authors thank Jason Geller for pointing them to this package.”
• Estimating power in (generalized) linear mixed models: An open introduction and tutorial in R (2020, methodology): “For the sake of completeness, Notebook 1 additionally includes examples using the extremely flexible simr package (Green & MacLeod, 2016) .”
• Sample Size Justification (2021, neutral): “…Maxwell, Kelley, & Rausch, 2008; Perugini, Gal-lucci, &Costantini, 2018), andanincreasingnumberof appliedtutorialsforspecifictests(Brysbaert&Stevens, 2018;DeBruine&Barr,2019;P.Green&MacLeod, 2016; Kruschke, 2013; Lakens & Caldwell, 2021; Schoe-mann, Boulton, &Short, 2017; Westfalletal., 2014).”
• Microplastics in bivalves and their habitat in relation to shellfish aquaculture proximity in coastal British Columbia, Canada (2019, methodology): “All simulations were run using the package simr (Green & MacLeod 2016), which allows statistical power calculations for mixed-effects models through repeated simulation of a given model/experimental design, thereby enabling the user to calculate power curves to assess trade-offs between power and…”
• Cognitive state dependent enhancement of cognitive control with transcranial magnetic stimulation (2026, unknown): “…of the behavioural state at the time of stimulation, our sample size was determined via power analysis of (generalised) linear mixed effects models 41,42 to achieve 80% statistical power and targeting a moderate effect size ( p2 = 0.08) based on DLPFC-neuromodulation studies in cognition and…”