When estimating causal effects using observational data, it is desirable to replicate a
randomized experiment as closely as possible by obtaining treated and control groups with …

Background In intervention trials, only randomization guarantees equal distributions of all
known and unknown patient characteristics between an intervention group and a control …

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or
mean imputation, only work under highly restrictive conditions, which are often not met in …

This paper studies the long-term impact of entrepreneurship education and training in high
school on entrepreneurial entry, performance, and survival. Using propensity score …

Case Study Research: Principles and Practices aims to provide a general understanding of
the case study method as well as specific tools for its successful implementation. These tools …

How can scholars select cases from a large universe for in-depth case study analysis?
Random sampling is not typically a viable approach when the total number of cases to be …

In this second edition of Counterfactuals and Causal Inference, completely revised and
expanded, the essential features of the counterfactual approach to observational data …

This study examines whether auditor industry specialization, measured using the auditor's
within‐industry market share, improves audit quality and results in a fee premium. After …

Official sanctioning of students by the criminal justice system is a long-hypothesized source
of educational disadvantage, but its explanatory status remains unresolved. Few studies of …

Matching is an R package which provides functions for multivariate and propensity score
matching and for finding optimal covariate balance based on a genetic search algorithm. A …