English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Linear mixed effects models (LMMs) are a popular and powerful tool foranalyzing clustered or repeated observations for numeric outcomes. LMMs consistof a fixed and a random component, specified in the model through theirrespective design matrices. Checking if the two design matrices are correctlyspecified is crucial since mis-specifying them can affect the validity andefficiency of the analysis. We show how to use random processes defined ascumulative sums of appropriately ordered model's residuals to test if thefunctional form of the fitted LMM is correctly specified. We show how theseprocesses can be used to test goodness-of-fit of the functional form of theentire model, or only its fixed and/or random component. Inspecting plots ofthe proposed processes is shown to be highly informative about the potentialmis-specification of the functional form of the model, providing clues forpotential improvement of the model's fit. We show how the visual inspection canbe objectified by using a novel procedure for estimating $p$-values which canbe based on sign-flipping/bootstrap or simulations and show its validity byusing theoretical results and a large Monte Carlo simulation study. Theproposed methodology can be used with LMMs with multi-level or crossed randomeffects.% and could also be extended to generalized LMMs.

Goodness-of-fit tests for functional form of Linear Mixed effects Models