We show that the Anderson-Rubin (AR) statistic is the sum of two independent piv-otal statistics. One statistic is a score statistic that tests location and the other statistictests misspecification. The chi-squared distribution of the location statistic has a degreesof freedom parameter that is...

In the regression discontinuity design, it is common practice to asses the credibility of the design by testing whether the means of baseline covariates do not change at the cutoff (or threshold) of the running variable. This practice is partly motivated by the stronger implication derived by...

In the regression discontinuity design (RDD), it is common practice to asses the credibility of the design by testing whether the means of baseline covariates do not change at the cutoff (or threshold) of the running variable. This practice is partly motivated by the stronger implication derived...

Children are seldom accounted for in household behavioural models. They are usually assumed to have neither the capacity nor the power to influence the household decision process. The literature on collective models has so far incorporated children through the caring preferences of their parents...

This paper proposes an asymptotically valid permutation test for a testable implication of the identification assumption in the regression discontinuity design (RDD). Here, by testable implication, we mean the requirement that the distribution of observed baseline covariates should not change...

This paper deals with the Bayesian analysis of graphical models of marginal independence for three way contingency tables. Each marginal independence model corresponds to a particular factorization of the cell probabilities and a conjugate analysis based on Dirichlet prior can be performed. We...

Let (omega,F,P) be a probability space. For each G in F, define G as the s-field generated by G and those sets f in F satisfying P(f) in {0, 1}. Conditions for P to be atomic on the intersection of the complements of Ai for i=1,..,k, with A1, . . . ,Ak in F sub-s-fields, are given. Conditions...

In observational studies, the non-parametric estimation of a binary treatment effect is often performed by matching each treated individual with a control unit which is similar in observed characteristics (covariates). In practical applications, the reservoir of covariates available may be...

We introduce a Bayesian approach to model assessment in the class of graphical vector autoregressive (VAR) processes. Due to the very large number of model structures that may be considered, simulation based inference, such as Markov chain Monte Carlo, is not feasible. Therefore, we derive an...

Causal discovery algorithms aim to identify causal relations from observational data and have become a popular tool for analysing genetic regulatory systems. In this work, we applied causal discovery to obtain novel insights into the genetic regulation underlying head-and-neck squamous cell...