9 citations · 11 across the 5 of their papers we have counts for
6 papers
Small area learning
Katarzyna Reluga, Nicola Salvati, Setareh Ranjbar +2
Small area estimation (SAE) traditionally borrows strength across domains through a prespecified working model. We introduce small area learning (SAL), a learner-agnostic framework…
A unified analysis of regression adjustment in randomized experiments
Katarzyna Reluga, Ting Ye, Qingyuan Zhao
Regression adjustment is broadly applied in randomized trials under the premise that it usually improves the precision of a treatment effect estimator. However, previous work has s…
Simple bootstrap for linear mixed effects under model misspecification
Katarzyna Reluga, Stefan Sperlich
Linear mixed effects are considered excellent predictors of cluster-level parameters in various domains. However, previous work has shown that their performance can be seriously af…
Post-selection inference for linear mixed model parameters using the conditional Akaike information criterion
Gerda Claeskens, Katarzyna Reluga, Stefan Sperlich
We investigate the issue of post-selection inference for a fixed and a mixed parameter in a linear mixed model using a conditional Akaike information criterion as a model selection…
Simultaneous Inference for Empirical Best Predictors with a Poverty Study in Small Areas
Katarzyna Reluga, María-José Lombardía, Stefan Sperlich
Today, generalized linear mixed models are broadly used in many fields. However, the development of tools for performing simultaneous inference has been largely neglected in this d…
Simultaneous inference for linear mixed model parameters with an application to small area estimation
Katarzyna Reluga, María José Lombardía, Stefan Andreas Sperlich
Over the past decades, linear mixed models have attracted considerable attention in various fields of applied statistics. They are popular whenever clustered, hierarchical or longi…