Generalized score test of homogeneity for mixed effects models

Many important problems in psychology and biomedical studies require testing for overdispersion, correlation and heterogeneity in mixed effects and latent variable models, and score tests are particularly useful for this purpose. But the existing testing procedures depend on restrictive assumptions. In this paper we propose a class of test statistics based on a general mixed effects model to test the homogeneity hypothesis that all of the variance components are zero. Under some mild conditions, not only do we derive asymptotic distributions of the test statistics, but also propose a resampling procedure for approximating their asymptotic distributions conditional on the observed data. To overcome the technical challenge, we establish an invariance principle for random quadratic forms indexed by a parameter. A simulation study is conducted to investigate the empirical performance of the test statistics. A real data set is analyzed to illustrate the application of our theoretical results.Comment: Published at http://dx.doi.org/10.1214/009053606000000380 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

An accurate test for homogeneity of odds ratios based on Cochran's Q-statistic

Background: A frequently used statistic for testing homogeneity in a meta-analysis of K independent studies is Cochran's Q. For a standard test of homogeneity the Q statistic is referred to a chi-square distribution with K - 1 degrees of freedom. For the situation in which the effects of the studies are logarithms of odds ratios, the chi-square distribution is much too conservative for moderate size studies, although it may be asymptotically correct as the individual studies become large. Methods: Using a mixture of theoretical results and simulations, we provide formulas to estimate the shape and scale parameters of a gamma distribution to t the distribution of Q. Results: Simulation studies show that the gamma distribution is a good approximation to the distribution for Q. Conclusions: : Use of the gamma distribution instead of the chi-square distribution for Q should eliminate inaccurate inferences in assessing homogeneity in a meta-analysis. (A computer program for implementing this test is provided.) This hypothesis test is competitive with the Breslow-Day test both in accuracy of level and in power

Understanding Price Variation Across Stores and Supermarket Chains: Some Implications for CPI Aggregation Methods

The empirical literature on price indices consistently finds that aggregation methods have a considerable impact, particularly when scanner data are used. This paper outlines a novel approach to test for the homogeneity of goods and hence for the appropriateness of aggregation. A hedonic regression framework is used to test for item homogeneity across four supermarket chains and across stores within each of these supermarket chains. We find empirical support for the aggregation of prices across stores which belong to the same supermarket chain. Support was also found for the aggregation of prices across three of the four supermarket chains.Price indexes; aggregation; scanner data; unit values; item homogeneity; hedonics

A power comparison of homogeneity tests in mixtures of exponentials

The empirical power of several test procedures is studied which test for homogeneity against mixtures of exponential distributions. --

The Homogeneity Scale of the universe

In this study, we probe the cosmic homogeneity with the BOSS CMASS galaxy sample in the redshift region of $0.43 < z < 0.7$. We use the normalised counts-in-spheres estimator $\mathcal{N}(<r)$ and the fractal correlation dimension $\mathcal{D}_{2}(r)$ to assess the homogeneity scale of the universe. We verify that the universe becomes homogenous on scales greater than $\mathcal{R}_{H} \simeq 64.3\pm1.6\ h^{-1}Mpc$, consolidating the Cosmological Principle with a consistency test of $\Lambda$CDM model at the percentage level. Finally, we explore the evolution of the homogeneity scale in redshift.Comment: 5 pages, 2 figures, Talk presented at The 51th Rencontres de Moriond, March 19-26, 2016, La Thuile, Italy; to appear in the Moriond Conference Proceeding

Testing Homogeneity of Time-Continuous Rating Transitions

Banks could achieve substantial improvements of their portfolio credit risk assessment by estimating rating transition matrices within a time-continuous Markov model, thereby using continuous-time rating transitions provided by internal rating systems instead of discrete-time rating information. A non-parametric test for the hypothesis of time-homogeneity is developed. The alternative hypothesis is multiple structural change of transition intensities, i.e. time-varying transition probabilities. The partial-likelihood ratio for the multivariate counting process of rating transitions is shown to be asymptotically c2 -distributed. A Monte Carlo simulation finds both size and power to be adequate for our example. We analyze transitions in credit-ratings in a rating system with 8 rating states and 2743 transitions for 3699 obligors observed over seven years. The test rejects the homogeneity hypothesis at all conventional levels of significance. --Portfolio credit risk,Rating transitions,Markov model,time-homogeneity,partial likelihood