• Publications
  • Influence
Statistics and Causal Inference
Abstract Problems involving causal inference have dogged at the heels of statistics since its earliest days. Correlation does not imply causation, and yet causal conclusions drawn from a carefully
Discrete Multivariate Analysis: Theory and Practice
TLDR
Discrete Multivariate Analysis is a comprehensive text and general reference on the analysis of discrete multivariate data, particularly in the form of multidimensional tables, and contains a wealth of material on important topics.
Robust regression using iteratively reweighted least-squares
The rapid development of the theory of robust estimation (Huber, 1973) has created a need for computational procedures to produce robust estimates. We will review a number of different computational
An Exponential Family of Probability Distributions for Directed Graphs
TLDR
An exponential family of distributions that can be used for analyzing directed graph data is described, and several special cases are discussed along with some possible substantive interpretations.
DIF DETECTION AND DESCRIPTION: MANTEL‐HAENSZEL AND STANDARDIZATION1,2
At the Educational Testing Service, the Mantel-Haenszel procedure is used for differential item functioning (DIF) detection and the standardization procedure is used to describe DIF. This report
CAUSAL INFERENCE, PATH ANALYSIS AND RECURSIVE STRUCTURAL EQUATIONS MODELS
Rubin's model for causal inference in experiments and observational studies is enlarged to analyze the problem of “causes causing causes” and is compared to path analysis and recursive structural
Population Invariance and the Equatability of Tests: Basic Theory and The Linear Case
How does the fact that two tests should not be equated manifest itself? This paper addresses this question through the study of the degree to which equating functions fail to exhibit population
...
...