Joseph W. McKean

TL;DR: In this paper, Rank-Based Analyses Scale Problem Placement Test for the Behrens-Fisher Problem Efficiency and Optimal Scores Adaptive Rank Scores Tests Regression I Simple linear regression Multiple linear regression Linear Models Aligned Rank Tests Bootstrap Nonparametric Regression Correlation ANOVA and ANCOVA One-Way ANOVA Multi-Way Crossed Factorial Design ANCO VA Methodology for Type III Hypotheses Testing Ordered Alternatives Multi-Sample Scale Problem Time-to-Event Analysis Kaplan-Meier and Log Rank Test Cox Proportional

TL;DR: In this paper, the effects of autocorrelated errors on Type I error in ordinary least-squares models are clarified, and it is shown that under certain conditions, distortion in type I error is far less than is predicted by asymptotic theory.

TL;DR: In this paper, four different approaches, based on ranks, to testing hypotheses are unified through the geometry of the linear model and various tests are identified with different but algebraically equivalent forms of the classical F test.

TL;DR: In this article, the authors define a new notion of order statistics and ranks for multivariate data based on density estimation and define a class of multivariate estimators of location that can be regarded as multivariate L-estimators.

TL;DR: In this article, the authors explore the properties of residuals from a rank-based fit of the model and present diagnostic techniques that detect outlying cases and cases that have an influential effect on the rankbased fit.