This paper considers statistical inference for additive partial linear models when the linear covariate is measured with error. To improve the accuracy of the normal approximation based confidence intervals, we develop an empirical likelihood based statistic, which is shown to be asymptotically chi-square distributed. We emphasize the finite-sample performance of the proposed method by conducti...

Although Cox proportional hazards regression is the default analysis for time to event data, there is typically uncertainty about whether the effects of a predictor are more appropriately characterized by a multiplicative or additive model. To accommodate this uncertainty, we place a model selection prior on the coefficients in an additive-multiplicative hazards model. This prior assigns positi...

Let Γ be a Borel probability measure on R and (T, C, Q) a nonatomic probability space. Define H = {H ∈ C : Q(H) > 0}. In some economic models, the following condition is requested. There are a probability space (Ω,A, P ) and a real process X = {Xt : t ∈ T} satisfying for each H ∈ H, there is AH ∈ A with P (AH) = 1 such that t 7→ X(t, ω) is measurable and Q ( {t : X(t, ω) ∈ ·} | H ) = Γ(·) for ω...

We present a coherent Bayesian framework for selection of the most likely model from the five genetic models (genotypic, additive, dominant, co-dominant, and recessive) commonly used in genetic association studies. The approach uses a polynomial parameterization of genetic data to simultaneously fit the five models and save computations. We provide a closed-form expression of the marginal likel...

Multivariate models are of great importance in theoretical and applied quantitative genetics. We extend quantitative genetic theory to accommodate situations in which there is linear feedback or recursiveness between the phenotypes involved in a multivariate system, assuming an infinitesimal, additive, model of inheritance. It is shown that structural parameters defining a simultaneous or recur...

This study examined the efficacy of peak-power estimation equations in children using force platform data and determined whether allometric modeling offers a sounder alternative to estimating peak power in pediatric samples. Ninety one boys and girls aged 12-16 years performed 3 countermovement jumps (CMJ) on a force platform. Estimated peak power (PP(est)) was determined using the Harman et al...

We consider a class of semiparametric models for the covariate distribution and missing data mechanism for missing covariate and/or response data for general classes of regression models including generalized linear models and generalized linear mixed models. Ignorable and nonignorable missing covariate and/or response data are considered. The proposed semiparametric model can be viewed as a se...

We study a class of genetic models in which a quantitative trait determined by several additive loci is subject to temporally fluctuating selection. Selection on the trait is assumed to be stabilizing but with an optimum that varies periodically and might be perturbed stochastically. The population mates at random, is infinitely large and has discrete generations. We pursue a statistical and nu...