Joint selection in mixed models using regularized PQL
The application of generalized linear mixed models presents some major challenges for
both estimation, due to the intractable marginal likelihood, and model selection, as we …
both estimation, due to the intractable marginal likelihood, and model selection, as we …
[HTML][HTML] A lasso and a regression tree mixed-effect model with random effects for the level, the residual variance, and the autocorrelation
S Nestler, S Humberg - psychometrika, 2022 - Springer
Research in psychology is experiencing a rapid increase in the availability of intensive
longitudinal data. To use such data for predicting feelings, beliefs, and behavior, recent …
longitudinal data. To use such data for predicting feelings, beliefs, and behavior, recent …
[HTML][HTML] Statistical modeling of surveillance data to identify correlates of urban malaria risk: A population-based study in the Amazon Basin
RM Corder, GA Paula, A Pincelli, MU Ferreira - PLoS One, 2019 - journals.plos.org
Despite the recent malaria burden reduction in the Americas, focal transmission persists
across the Amazon Basin. Timely analysis of surveillance data is crucial to characterize high …
across the Amazon Basin. Timely analysis of surveillance data is crucial to characterize high …
Gradient tree boosting for hierarchical data
M Salditt, S Humberg, S Nestler - Multivariate Behavioral Research, 2023 - Taylor & Francis
Gradient tree boosting is a powerful machine learning technique that has shown good
performance in predicting a variety of outcomes. However, when applied to hierarchical (eg …
performance in predicting a variety of outcomes. However, when applied to hierarchical (eg …
Hierarchical selection of fixed and random effects in generalized linear mixed models
In many applications of generalized linear mixed models (GLMMs), there is a hierarchical
structure in the effects that needs to be taken into account when performing variable …
structure in the effects that needs to be taken into account when performing variable …
[PDF][PDF] Sparse Multilevel Regression (and Poststratification (sMRP))
Multilevel models have long played an important role in a variety of social sciences. We
extend this framework by bring to bear recent developments in the machine learning …
extend this framework by bring to bear recent developments in the machine learning …
Joint modeling of playing time and purchase propensity in massively multiplayer online role-playing games using crossed random effects
Joint modeling of playing time and purchase propensity in massively multiplayer online role-playing
games using crossed random e Page 1 The Annals of Applied Statistics 2023, Vol. 17, No. 3 …
games using crossed random e Page 1 The Annals of Applied Statistics 2023, Vol. 17, No. 3 …
A large-scale constrained joint modeling approach for predicting user activity, engagement, and churn with application to freemium mobile games
We develop a constrained extremely zero inflated joint (CEZIJ) modeling framework for
simultaneously analyzing player activity, engagement, and dropouts (churns) in app-based …
simultaneously analyzing player activity, engagement, and dropouts (churns) in app-based …
Personality, body condition and breeding experience drive sociality in a facultatively social bird
Adopting different behavioural strategies may reduce within-group conflict, selecting for
behavioural consistency ('personality'). Personality may also affect grouping tendencies. The …
behavioural consistency ('personality'). Personality may also affect grouping tendencies. The …
Random effects misspecification can have severe consequences for random effects inference in linear mixed models
There has been considerable and controversial research over the past two decades into
how successfully random effects misspecification in mixed models (ie assuming normality for …
how successfully random effects misspecification in mixed models (ie assuming normality for …