Linear Mixed Effects Model

By A. Galecki, T. Burzykowski. Encyclopedia of Gerontology and Population Aging, 2021

128 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/120e6520a7fe9f5f7ecb54b981cb3e06d1ac6019

How researchers see this paper

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

In Computer Networks and Communications

1. Anders Søgaard
2. Stella Frank

In Management Science and Operations Research

1. Anders Søgaard
2. Artur Kulmizev
3. Ellie Pavlick

In Statistics and Probability

1. Anders Søgaard
2. Daniel Hershcovich
3. Ellie Pavlick

Citations in the corpus

• Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color (2021, methodology): “11 We then fit a Linear Mixed Effects Model (Gałecki and Burzykowski, 2013) to the features listed above, with RSA score (Table 1) as the response variable, and model type as a random effect.”