5 papers
Linear Regression from 1-bit Quantized Data
Daniel Hill, Martin Slawski
Motivated by the prevalence of environments in which data is abundant while resources for storage and/or transmission might be scarce, we study linear regression when predictors, t…
Causal Secondary Analysis of Linked Data in the Presence of Mismatch Error
Martin Slawski
The increased prevalence of observational data and the need to integrate information from multiple sources are critical challenges in contemporary data analysis. Record linkage is…
Relaxing the Assumption of Strongly Non-Informative Linkage Error in Secondary Regression Analysis of Linked Files
Priyanjali Bukke, Martin Slawski
Data analysis of files that are a result of linking records from multiple sources are often affected by linkage errors. Records may be linked incorrectly, or their links may be mis…
Lasso Penalization for High-Dimensional Beta Regression Models: Computation, Analysis, and Inference
Niloofar Ramezani, Martin Slawski
Beta regression is commonly employed when the outcome variable is a proportion. Since its conception, the approach has been widely used in applications spanning various scientific…
Identifiability in Unlinked Linear Regression: Some Results and Open Problems
Fadoua Balabdaoui, Martin Slawski, Jonathan Steffani
A tacit assumption in classical linear regression problems is the full knowledge of the existing link between the covariates and responses. In Unlinked Linear Regression (ULR) this…