Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease.

For count data, though a zero-inflated model can work perfectly well with an excess of zeroes and the generalized Poisson model can tackle over- or under-dispersion, most models cannot simultaneously deal with both zero-inflated or zero-deflated data and over- or under-dispersion. Ear diseases are important in healthcare, and falls into this kind of count data. This paper introduces a generalized Poisson Hurdle model that work with count data of both too many/few zeroes and a sample variance not equal to the mean. To estimate parameters, we use the generalized method of moments. In addition, the asymptotic normality and efficiency of these estimators are established. Moreover, this model is applied to ear disease using data gained from the New South Wales Health Research Council in 1990. This model performs better than both the generalized Poisson model and the Hurdle model.

Pst DC3000 infection alleviates subsequent freezing and heat injury to host plants via a salicylic acid-dependent pathway in Arabidopsis.

Abiotic stresses greatly affect the immunity of plants. However, it is unknown whether pathogen infection affects abiotic stress tolerance of host plants. Here, the effect of defense response on cold and heat tolerance of host plants was investigated in Pst DC3000-infected Arabidopsis plants, and it was found that the pathogen-induced defense response could alleviate the injury caused by subsequent cold and heat stress (38°C). Transcriptomic sequencing plus RT-qPCR analyses showed that some abiotic stress genes are up-regulated in transcription by pathogen infection, including cold signaling components ICE1, CBF1, and CBF3, and some heat signaling components HSFs and HSPs. Moreover, the pathogen-induced alleviation of cold and heat injury was lost in NahG transgenic line (SA-deficient), sid2-2 and npr1-1 mutant plants, and pathogen-induced expression of cold and heat tolerance-related genes such as CBFs and HSPs, respectively, was lost or compromised in these plants, indicating that salicylic acid signaling pathway is required for the alleviation of cold and heat injury by pathogen infection. In short, our current work showed that in fighting against pathogens, host plants also enhance their cold and heat tolerance via a salicylic acid-dependent pathway.

Measuring Associations of the Department of Veterans Affairs' Suicide Prevention Campaign on the Use of Crisis Support Services.

Campaigns have become popular in public health approaches to suicide prevention; however, limited empirical investigation of their impact on behavior has been conducted. To address this gap, utilization patterns of crisis support services associated with the Department of Veterans Affairs' Veterans Crisis Line (VCL) suicide prevention campaign were examined. Daily call data for the National Suicide Prevention Lifeline, VCL, and 1-800-SUICIDE were modeled using a novel semi-varying coefficient method. Analyses reveal significant increases in call volume to both targeted and broad resources during the campaign. Findings underscore the need for further research to refine measurement of the effects of these suicide prevention efforts.

Double-smoothing for Varying Coefficient Models.

Moderation analyses are widely used in biomedical and psychosocial research to investigate differential treatment effects, with moderators frequently identified through testing the significance of the interaction between the predictor and the potential moderator under strong parametric assumptions. Without imposing any parametric forms on how the moderators may affect the relationship between predictors and responses, varying coefficient models address this fundamental problem of strong parametric assumptions with current practice of moderation analysis and provide a much broader class of models for complex moderation relationships. Local polynomial, especially local linear, methods are commonly used in estimating the varying coefficient models. Recently, a double-smoothing (DS) local linear method has been proposed for nonparametric regression models, with nice properties compared to local linear and local cubic methods. In this paper, we generalize DS to varying coefficient models, and show that it holds similar advantages over local linear and local cubic methods.

A baseline-free procedure for transformation models under interval censorship.

An important property of Cox regression model is that the estimation of regression parameters using the partial likelihood procedure does not depend on its baseline survival function. We call such a procedure baseline-free. Using marginal likelihood, we show that an baseline-free procedure can be derived for a class of general transformation models under interval censoring framework. The baseline-free procedure results a simplified and stable computation algorithm for some complicated and important semiparametric models, such as frailty models and heteroscedastic hazard/rank regression models, where the estimation procedures so far available involve estimation of the infinite dimensional baseline function. A detailed computational algorithm using Markov Chain Monte Carlo stochastic approximation is presented. The proposed procedure is demonstrated through extensive simulation studies, showing the validity of asymptotic consistency and normality. We also illustrate the procedure with a real data set from a study of breast cancer. A heuristic argument showing that the score function is a mean zero martingale is provided.