Power and Sample Size in Multilevel Linear Models
By Tom A. B. Snijders. 2005
495 citations recorded by the source corpus.
Subfields: Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/f73f3335ab99e13eee4276ed30dad79eaedba7dd
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Science and Operations Research
- John E. Mathieu
- Robert A. I. Davies
- A. Lorenzo-Arribas
- Lotte Meteyard
- Michael Hanslmaier
- Charles A. Scherbaum
- M. Marselle
- Gilad Chen
In Statistics and Probability
- Robert A. I. Davies
- A. Lorenzo-Arribas
- Lotte Meteyard
- Michael Hanslmaier
- Charles A. Scherbaum
- John E. Mathieu
- P. Mcdermott
- Vivian L. Gadsden
Citations in the corpus
- Crime, fear and subjective well-being: How victimization and street crime affect fear and life satisfaction (2013, background): “This line of argument gains further weight by the fact that a low average number of respondents per cluster (as in the present case) limits the power to detect random slopes, but poses no problem for the tests of fixed coefficients (Snijders, 2005).”
- The Etiology of the Multilevel Paradigm in Management Research (2011, background): “Factors contributing to multilevel power also differ depending on the parameters of interest— that is, the variance of lower-level slopes versus unit intercepts or means (Snijders, 2005).”
- An Integrated Curriculum to Improve Mathematics, Language, and Literacy for Head Start Children (2011, background): “Relatively small amounts of variability (for general comparisons, see Raudenbush, Martinez, & Spybrook, 2007; Snijders, 2005) were detected between classrooms (M = 5.54%, SD = 1.87), the percentage never exceeding 7%.”
- Does perceived restorativeness mediate the effects of perceived biodiversity and perceived naturalness on emotional well-being following group walks in nature? (2016, background): “Third, power is important for multilevel analyses (Snijders, 2005).”
- Best practice guidance for linear mixed-effects models in psychological science (2019, methodology): “In addition, for LMMs, we can usefully consider the power to accurately estimate fixed effect coefficients, random effect variances, averages for particular sampling units or interactions across those units (Scherbaum & Ferreter, 2009; Snijders, 2005).”
- Estimating Statistical Power and Required Sample Sizes for Organizational Research Using Multilevel Modeling (2009, background): “As Snijders (2005) has noted, there are not clear formula for some general cases of complex multilevel models.”