Selecting the Best Linear Mixed Model Under REML
By Matthew J. Gurka. 2006
188 citations recorded by the source corpus.
Subfields: Genetics, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/967852f5ead153ebca88558c734ca1950fbb89f3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Genetics
- Danny Pfeffermann
- Philip V. Grice
- W. J. Peach
- K. Vincent
- Laura M. Stapleton
- Daniel M. McNeish
- J. Fowler
In Statistics and Probability
- Daniel M. McNeish
- Laura M. Stapleton
- Danny Pfeffermann
- Philip V. Grice
- W. J. Peach
- K. Vincent
- R. Silverman
- J. Fowler
Citations in the corpus
- On the Unnecessary Ubiquity of Hierarchical Linear Modeling (2017, background): “This topic has been recently researched (e.g., Gurka, 2006; Lukočienė, Varriale, & Vermunt, 2010; Whittaker & Furlow, 2009) although no consensus has been reached.”
- New important developments in small area estimation (2013, methodology): “Gurka (2006) validates by simulations that one can use also in this case the mAIC with ψ̂REML, despite the use of different fixed effects design matrices under different models.”
- Reproductive success of house sparrows along an urban gradient (2008, methodology): “As information theoretic approaches cannot generally be used to assess the importance of fixed factors in mixed models (Verbeke & Molenberghs, 2000; Gurka, 2006), Wald tests were used to select significant predictors of nesting success.”