Application of Mixed Linear Models in the Analysis of Road Surface Features
Jurgita Židanavičiūtė
Vilnius Gediminas Technical University, Lithuania
Audrius Vaitkus
Vilnius Gediminas Technical University, Lithuania
Published 2015-12-20


mixed linear models
repeated measurements
clustered longitudinal data

How to Cite

Židanavičiūtė J. and Vaitkus A. (2015) “Application of Mixed Linear Models in the Analysis of Road Surface Features”, Lithuanian Journal of Statistics, 54(1), pp. 101-109. doi: 10.15388/LJS.2015.13885.


The data were collected by researchers at the Road Research Institute, in a study investigating the impact of differentfactors on road surface strength. In this statistical analysis, we apply linear mixed models (LMMs) to clustered longitudinal data, inwhich the units of analysis (points in the road) are nested within clusters (sample of four different road segments), and repeatedmeasures of road strength in these different points are collected over time with unequally spaced time intervals. The data arebalanced – each cluster has the same number of units, which are measured at the same number of time points. Because of correlateddata and different clusters in which data could be correlated, linear regression models are not appropriate here, and therefore linearmixed models are applied.

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