This Title All WIREs
How to cite this WIREs title:
WIREs Comp Stat

Fixed and random effects models

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract Traditional linear regression at the level taught in most introductory statistics courses involves the use of ‘fixed effects’ as predictors of a particular outcome. This treatment of the independent variable is often sufficient. However, as research questions have become more sophisticated, coupled with the rapid advancement in computational abilities, the use of random effects in statistical modeling has become more commonplace. Treating predictors in a model as a random effect allows for more general conclusions—a great example being the treatment of the studies that comprise a meta‐analysis as random rather than fixed. In addition, utilization of random effects allows for more accurate representation of data that arise from complicated study designs, such as multilevel and longitudinal studies, which in turn allows for more accurate inference on the fixed effects that tend to be of primary interest. It is important to note the distinctions between fixed and random effects in the most general of settings, while also knowing the benefits and risks to their simultaneous use in specific yet common situations. WIREs Comput Stat 2012, 4:181–190. doi: 10.1002/wics.201 This article is categorized under: Statistical Models > Linear Models Statistical Models > Classification Models

Model‐Predicted Mean and Individual Behavior Profiles Over Time. Solid bold lines represent model‐predicted mean (fixed effects) profiles for white children whose mothers were 30 years old and had 14 years of education (black = full‐term; red = late preterm). Dashed lines indicate individual trajectories as estimated from the random effects included in the model.

[ Normal View | Magnified View ]

Browse by Topic

Statistical Models > Classification Models
Statistical Models > Linear Models

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts