42 citations · 81 across the 21 of their papers we have counts for
9 papers · 1 filter
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…
Accounting for Mismatch Error in Small Area Estimation with Linked Data
Enrico Fabrizi, Nicola Salvati, Martin Slawski
In small area estimation different data sources are integrated in order to produce reliable estimates of target parameters (e.g., a mean or a proportion) for a collection of small…
A General Framework for Regression with Mismatched Data Based on Mixture Modeling
Martin Slawski, Brady T. West, Priyanjali Bukke +3
Data sets obtained from linking multiple files are frequently affected by mismatch error, as a result of non-unique or noisy identifiers used during record linkage. Accounting for…
Tensor Completion for Causal Inference with Multivariate Longitudinal Data: A Reevaluation of COVID-19 Mandates
Jonathan Auerbach, Martin Slawski, Shixue Zhang
We propose a new method that uses tensor completion to estimate causal effects with multivariate longitudinal data, data in which multiple outcomes are observed for each unit and t…