A Penalty Approach to Differential Item Functioning in Rasch Models

A new diagnostic tool for the identification of differential item functioning (DIF) is proposed. Classical approaches to DIF allow to consider only few subpopulations like ethnic groups when investigating if the solution of items depends on the membership to a subpopulation. We propose an explicit model for differential item functioning that includes a set of variables, containing metric as well as categorical components, as potential candidates for inducing DIF. The ability to include a set of covariates entails that the model contains a large number of parameters. Regularized estimators, in particular penalized maximum likelihood estimators, are used to solve the estimation problem and to identify the items that induce DIF. It is shown that the method is able to detect items with DIF. Simulations and two applications demonstrate the applicability of the method

Unionism and peer-referencing

This study assesses the “fair-wage-effort” hypothesis, by examining (a) the relationship between relative wage comparisons and job satisfaction and quitting intensions, and (b) the relative ranking of stated effort inducing-incentives, in a novel dataset of unionised and non-unionised European employees. By distinguishing between downward and upward-looking wage comparisons, it is shown that wage comparisons to similar workers exert an asymmetric impact on the job satisfaction of union workers, a pattern consistent with inequity-aversion and conformism to the reference point. Moreover, union workers evaluate peer observation and good industrial relations more highly than payment and other incentives. In contrast, non-union workers are found to be more status-seeking in their satisfaction responses and less dependent on their peers in their effort choices The results are robust to endogenous union membership, considerations of generic loss aversion and across different tenure profiles. They are supportive of the individual egalitarian bias of collective wage determination and self-enforcing effort norms.EPICURUS, a project supported by the European Commission through the 5th Framework Programme “Improving Human Potential” (contract number: HPSE-CT-2002-00143

A statistical framework for testing functional categories in microarray data

Ready access to emerging databases of gene annotation and functional pathways has shifted assessments of differential expression in DNA microarray studies from single genes to groups of genes with shared biological function. This paper takes a critical look at existing methods for assessing the differential expression of a group of genes (functional category), and provides some suggestions for improved performance. We begin by presenting a general framework, in which the set of genes in a functional category is compared to the complementary set of genes on the array. The framework includes tests for overrepresentation of a category within a list of significant genes, and methods that consider continuous measures of differential expression. Existing tests are divided into two classes. Class 1 tests assume gene-specific measures of differential expression are independent, despite overwhelming evidence of positive correlation. Analytic and simulated results are presented that demonstrate Class 1 tests are strongly anti-conservative in practice. Class 2 tests account for gene correlation, typically through array permutation that by construction has proper Type I error control for the induced null. However, both Class 1 and Class 2 tests use a null hypothesis that all genes have the same degree of differential expression. We introduce a more sensible and general (Class 3) null under which the profile of differential expression is the same within the category and complement. Under this broader null, Class 2 tests are shown to be conservative. We propose standard bootstrap methods for testing against the Class 3 null and demonstrate they provide valid Type I error control and more power than array permutation in simulated datasets and real microarray experiments.Comment: Published in at http://dx.doi.org/10.1214/07-AOAS146 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Insecurity of Property Rights and Matching in the Tenancy Market

This paper analyzes the functioning of land rental markets in the Dominican Republic using a new data set collected specifically to characterize the entire market. We analyze the choice of the landlords and the tenants in the search for the optimal partner. We show how insecure property rights leads to segmentation in the tenancy markets along socio-economic group and hence severely limits access to land for the rural poor.insecurity of property rights, land markets, matching, Risk and Uncertainty,