Generalized linear mixed models: a practical guide for ecology and evolution
How should ecologists and evolutionary biologists analyze nonnormal data that involve
random effects? Nonnormal data such as counts or proportions often defy classical statistical …
random effects? Nonnormal data such as counts or proportions often defy classical statistical …
[HTML][HTML] Modeling individual differences in randomized experiments using growth models: Recommendations for design, statistical analysis and reporting of results of …
H Hesser - Internet interventions, 2015 - Elsevier
Growth models (also known as linear mixed effects models, multilevel models, and random
coefficients models) have the capability of studying change at the group as well as the …
coefficients models) have the capability of studying change at the group as well as the …
On the unnecessary ubiquity of hierarchical linear modeling.
In psychology and the behavioral sciences generally, the use of the hierarchical linear
model (HLM) and its extensions for discrete outcomes are popular methods for modeling …
model (HLM) and its extensions for discrete outcomes are popular methods for modeling …
Moderate alcohol consumption as risk factor for adverse brain outcomes and cognitive decline: longitudinal cohort study
Objectives To investigate whether moderate alcohol consumption has a favourable or
adverse association or no association with brain structure and function. Design …
adverse association or no association with brain structure and function. Design …
[책][B] Joint models for longitudinal and time-to-event data: With applications in R
D Rizopoulos - 2012 - books.google.com
In longitudinal studies it is often of interest to investigate how a marker that is repeatedly
measured in time is associated with a time to an event of interest, eg, prostate cancer studies …
measured in time is associated with a time to an event of interest, eg, prostate cancer studies …
[책][B] Linear mixed-effects model
A Gałecki, T Burzykowski, A Gałecki, T Burzykowski - 2013 - Springer
In Chap. 10, we presented linear models (LMs) models with fixed effects for correlated data.
They are examples of population-averaged models, because their mean-structure …
They are examples of population-averaged models, because their mean-structure …
[책][B] Missing data in clinical studies
G Molenberghs, M Kenward - 2007 - books.google.com
Missing Data in Clinical Studies provides a comprehensive account of the problems arising
when data from clinical and related studies are incomplete, and presents the reader with …
when data from clinical and related studies are incomplete, and presents the reader with …
The estimation of item response models with the lmer function from the lme4 package in R
In this paper we elaborate on the potential of the lmer function from the lme4 package in R
for item response (IRT) modeling. In line with the package, an IRT framework is described …
for item response (IRT) modeling. In line with the package, an IRT framework is described …
frailtypack: an R package for the analysis of correlated survival data with frailty models using penalized likelihood estimation or parametrical estimation
V Rondeau, Y Marzroui, JR Gonzalez - Journal of Statistical Software, 2012 - jstatsoft.org
Frailty models are very useful for analysing correlated survival data, when observations are
clustered into groups or for recurrent events. The aim of this article is to present the new …
clustered into groups or for recurrent events. The aim of this article is to present the new …