626 citations · 830 across the 19 of their papers we have counts for
21 papers
Hole or grain? A Section Pursuit Index for Finding Hidden Structure in Multiple Dimensions
Ursula Laa, Dianne Cook, Andreas Buja +1
Multivariate data is often visualized using linear projections, produced by techniques such as principal component analysis, linear discriminant analysis, and projection pursuit. A…
All of Linear Regression
Arun K. Kuchibhotla, Lawrence D. Brown, Andreas Buja +1
Least squares linear regression is one of the oldest and widely used data analysis tools. Although the theoretical analysis of the ordinary least squares (OLS) estimator is as old,…
Model-free Study of Ordinary Least Squares Linear Regression
Arun K. Kuchibhotla, Lawrence D. Brown, Andreas Buja
Ordinary least squares (OLS) linear regression is one of the most basic statistical techniques for data analysis. In the main stream literature and the statistical education, the s…
Using Recursive Partitioning to Find and Estimate Heterogenous Treatment Effects In Randomized Clinical Trials
Richard A. Berk, Matthew Olson, Andreas Buja +1
Heterogeneous treatment effects can be very important in the analysis of randomized clinical trials. Heightened risks or enhanced benefits may exist for particular subsets of study…
Assumption Lean Regression
Richard A. Berk, Andreas Buja, Lawrence Brown +4
It is well known that models used in conventional regression analysis are commonly misspecified. A standard response is little more than a shrug. Data analysts invoke Box's maxim t…
Valid Post-selection Inference in Assumption-lean Linear Regression
Arun Kumar Kuchibhotla, Lawrence D. Brown, Andreas Buja +2
Construction of valid statistical inference for estimators based on data-driven selection has received a lot of attention in the recent times. Berk et al. (2013) is possibly the fi…