We describe an extension of the pseudo maximum likelihood (PML) estimation method developed by Skinner (1989) to multistage strati ̄ed cluster sampling designs, including ̄nite population and unequal probability sampling. We conduct simulation studies to evaluate the performance of the proposed estimator. The estimator is also compared to the general estimating equation (GEE) method for linear r...

This paper discusses the empirical likelihood ratio test for testing equality of medians of two distributions. Yu et al. (2011) proposed four forms of empirical likelihood ratio test for testing this hypothesis and one of them is based on the pooled sample median. The asymptotic distribution of the test statistic as derived in Yu et al (2011) differ from the one obtained in Nimbalkar and Rajars...

The problem of sequential testing of composite hypotheses is considered. Asymptotic expansions are constructed for the conditional error probabilities and expected sample sizes under “contamination” of the probability distribution of observations. To obtain these results a new approach based on approximation of the generalized likelihood ratio statistic by a specially constructed Markov chain i...

We describe a statistical hypothesis test for the presence of a signal based on the likelihood ratio statistic. We derive the test for one case of interest and also show that for that case the test works very well, even far out in the tails of the distribution. We also study extensions of the test to cases where there are multiple channels.

We consider a nonlinear polynomial regression model in which we wish to test the null hypothesis of structural stability in the regression parameters against the alternative of a break at an unknown time. We derive the extreme value distribution of a maximum–type test statistic which is asymptotically equivalent to the maximally selected likelihood ratio. AMS 2000 Subject Classification: Primar...

Abstract In many meta-analyses, the variable of interest is frequently a count outcome reported in an intervention and control group. Single- or double-zero studies are often observed this type data. Given setting, well-known Cochran’s Q statistic for testing homogeneity becomes undefined. paper, we propose two statistics risk ratio, particularly application case rare events meta-analysis. The ...

Imputation is a popular technique for handling missing data especially for plenty of missing values. Usually, the empirical log-likelihood ratio statistic under imputation is asymptotically scaled chi-squared because the imputing data are not i.i.d. Recently, a bias-corrected technique is used to study linear regression model with missing response data, and the resulting empirical likelihood ra...

For multilevel analyses (e.g., linear mixed models), researchers are often interested in pooling, interpreting, and testing both fixed effects and random effects. PROC MIANALYZE has two shortcomings in this regard. First, it cannot easily pool variance estimates. Second, the significance tests of these estimates are Wald-type tests that are inappropriate for testing variance estimates. Likeliho...

Pseudo empirical likelihood ratio confidence intervals for finite population parameters are based on asymptotic χ2 approximation to an adjusted pseudo empirical likelihood ratio statistic, with the adjustment factor related to the design effect. Calculation of the design effect involves variance estimation and hence requires second order inclusion probabilities. It also depends on how auxiliary...

For generalized linear models with multivariate response and natural link functions, likelihood ratio test of one-sided hypothesis on the regression parameter is considered under rather general conditions. The null-asymptotic distribution of the test statistic turns out to be chi-bar squared. The extension of the above results to include quasi-likellihood ratio test to incorporate over-dispersi...