Many statisticians have had the experience of fitting a linear model with uncorrelated errors, then adding a spatiallycorrelated error term (random effect) and finding that the estimates of the fixed-effect coefficients have changed substantially. We show that adding a spatially-correlated error term to a linear model is equivalent to adding a saturated collection of canonical regressors, the c...

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...

The results on optimal designs for diallel crosses are based on standard linear model assumptions where the general combining ability effects are taken as fixed. Recently Ghosh and Das (2003) proposed a random effects model that allows one to first estimate the variance components and then obtain the variances of these estimates. In this paper we first propose an unbiased estimate of the ratio ...

Words are reduced in spontaneous speech. If reductions are constrained by functional (i.e., perception and production) constraints, they should not be arbitrary. This hypothesis was tested by examing the pronunciations of highto mid-frequency words in a Dutch and a German spontaneous speech corpus. In logistic-regression models the "reduction likelihood" of a phoneme was predicted by fixed-effe...

The emerging technology of wearable inertial sensors has shown its advantages in collecting continuous longitudinal gait data outside laboratories. This freedom also presents challenges in collecting high-fidelity gait data. In the free-living environment, without constant supervision from researchers, sensor-based gait features are susceptible to variation from confounding factors such as gait...

In actuarial practice, regression models serve as a popular statistical tool for analyzing insurance data and tariff ratemaking. In this paper, we consider classical credibility models that can be embedded within the framework of mixed linear models. For inference about fixed effects and variance components, likelihood-based methods such as (restricted) maximum likelihood estimators are commonl...

We have established a method for systematic integration of multiple microarray datasets. The method was applied to two different sets of cancer profiling studies. The change of gene expression in cancer was expressed as 'effect size', a standardized index measuring the magnitude of a treatment or covariate effect. The effect sizes were combined to obtain the estimate of the overall mean. The st...

Effects of inbreeding of animal and dam on estimates of genetic parameters and predictions of breeding values for five productive and reproductive traits of Piedmontese cattle were studied. Traits were (a) age at first insemination, (b) age at first calving, (c) 120-day weight, (d) yearling weight of males, and (e) yearling weight of females. Data for animals born from 1970 to 1995 were used. I...

As with ordinary least squares regression or logistic regression, we can consider significance tests for individual estimates, such as intercepts, slopes, and their variances, as well as whether the full model accounts for a significant amount of variance in the dependent variable. In between, there is also the possibility of determining whether of subset of predictors contribute significantly....

A meta-analysis was conducted to investigate the effects of digital game-based learning (DGBL) in English as a foreign language (EFL) contexts. Twenty-five studies were included and they yielded a medium positive effect size (d = 0.695, p < .05 under the fixed-effect model; d = 0.777, p < .05 under the random-effects model), suggesting DGBL to be more effective than traditional instruction such...