Goodness-of-Fit Tests for the Gamma Distribution Based on the Empirical Laplace Transform

We propose a class of goodness-of-fit tests for the gamma distribution that utilizes the empirical Laplace transform. The consistency of the tests as well as their asymptotic distribution under the null hypothesis are investigated. As the decay of the weight function tends to infinity, the test statistics approach limit values related to the first non zero component of Neyman's smooth test for the gamma law. The new tests are compared with other omnibus tests for the gamma distribution.     

Assessing the treatment effect in a randomized controlled trial with extensive non‐adherence: the EVOLVE trial

Intention‐to‐treat (ITT) analysis is widely used to establish efficacy in randomized clinical trials. However, in a long‐term outcomes study where non‐adherence to study drug is substantial, the on‐treatment effect of the study drug may be underestimated using the ITT analysis. The analyses presented herein are from the EVOLVE trial, a double‐blind, placebo‐controlled, event‐driven cardiovascular outcomes study conducted to assess whether a treatment regimen including cinacalcet compared with placebo in addition to other conventional therapies reduces the risk of mortality and major cardiovascular events in patients receiving hemodialysis with secondary hyperparathyroidism. Pre‐specified sensitivity analyses were performed to assess the impact of non‐adherence on the estimated effect of cinacalcet. These analyses included lag‐censoring, inverse probability of censoring weights (IPCW), rank preserving structural failure time model (RPSFTM) and iterative parameter estimation (IPE). The relative hazard (cinacalcet versus placebo) of mortality and major cardiovascular events was 0.93 (95% confidence interval 0.85, 1.02) using the ITT analysis; 0.85 (0.76, 0.95) using lag‐censoring analysis; 0.81 (0.70, 0.92) using IPCW; 0.85 (0.66, 1.04) using RPSFTM and 0.85 (0.75, 0.96) using IPE. These analyses, while not providing definitive evidence, suggest that the intervention may have an effect while subjects are receiving treatment. The ITT method remains the established method to evaluate efficacy of a new treatment; however, additional analyses should be considered to assess the on‐treatment effect when substantial non‐adherence to study drug is expected or observed. Copyright © 2015 John Wiley & Sons, Ltd.     

Understanding the mobility chances of children from working-class backgrounds in Britain: How important are cognitive ability and locus of control?

Research in social stratification has shown that children from working-class backgrounds tend to obtain substantially lower levels of educational attainment and lower labor market positions than children from higher social class backgrounds. However, we still know relatively little about the micro-level processes that account for this empirical regularity. Our study examines the roles of two individual-level characteristics—cognitive ability and locus of control—in mediating the effect of individuals’ parental class background on their educational attainment and social class position in Britain. We find that cognitive ability mediates only about 35% of the total parental class effect on educational attainment and only about 20% of the total parental class effect on respondents’ social class position, net of their educational attainment. These findings contradict existing claims that differences in the life chances of children from different social class backgrounds are largely due to differences in cognitive ability. Moreover, we find that although individuals’ locus of control plays some role in mediating the parental class effect, its role is substantially smaller than the mediating role of cognitive ability. We measure individuals’ social class positions at different points in their careers—at labor market entry and at occupational maturity—and find that the mediating roles of cognitive ability and locus of control are remarkably stable across individuals’ working lives.     

Weighted Integral Test Statistics and Components of Smooth Tests of Fit

This paper considers families of statistics for testing the goodness-of-fit of various parametric models such as the normal, exponential or Poisson. Each family consists of weighted integrals over the squared modulus of some measure of deviation from the parametric model, expressed by means of an empirical transform of the data. Letting the rate of decay of the weight function tend to infinity, each test statistic, after a suitable rescaling, approaches a limit that is closely connected to the first non-zero component of Neyman's smooth test for the parametric model.     

Tests of Fit for Exponentiality based on the Empirical Laplace Transform

The Laplace transform \psi(t)=E[{\rm exp}(-tX)] of a random variable X with exponential density u exp( m u x ), x S 0, satisfies the equation (\lambda+t)\psi(t)-\lambda=0 , t S 0. We study the behavior of a class of consistent tests for exponentiality based on a suitably weighted integral of [({\hat\lambda}_n+t)\psi_n(t)-{\hat\lambda}_n]^2 , where {\hat\lambda}_n is the maximum-likelihood estimate of u , and é n is the empirical Laplace transform, each based on an i.i.d. sample X 1 , …, X n . As the decay of the weight function tends to infinity, the test statistic approaches the square of the first nonzero component of Neyman's smooth test for exponentiality. The new tests are compared with other omnibus tests for exponentiality.     

TRANSPARENCY IN MARKETS FOR EXPERIENCE GOODS: EXPERIMENTAL EVIDENCE

We propose an experimental design to investigate the role of information disclosure in the market for an experience good. The market is served by a duopoly of firms that choose both the quality and the price of their product. Consumers differ in their taste for quality and choose from which firm to buy. We compare four different treatments in which we vary the degree to which consumers are informed about quality. Contrary to theoretical predictions, firms do not differentiate quality under full information. Rather, both tend to offer products of similar, high quality, entailing more intense price competition than predicted by theory. Under no information, we observe a “lemons” outcome where quality is low. At the same time, firms manage to maintain prices substantially above marginal cost. In two intermediate treatments, quality is significantly higher than the no‐information level, and there is evidence that prices become better predictors of quality. Taken together these findings suggest that information disclosure is a more effective tool to raise welfare and consumer surplus than theory would lead one to expect. (JEL L15, C91, D82)