Marginal zero-inflated regression models for count data

Data sets with excess zeroes are frequently analyzed in many disciplines. A common framework used to analyze such data is the zero-inflated (ZI) regression model. It mixes a degenerate distribution with point mass at zero with a non-degenerate distribution. The estimates from ZI models quantify the effects of covariates on the means of latent random variables, which are often not the quantities of primary interest. Recently, marginal zero-inflated Poisson (MZIP; Long et al. [A marginalized zero-inflated Poisson regression model with overall exposure effects. Stat. Med. 33 (2014), pp. 5151–5165]) and negative binomial (MZINB; Preisser et al., 2016) models have been introduced that model the mean response directly. These models yield covariate effects that have simple interpretations that are, for many applications, more appealing than those available from ZI regression. This paper outlines a general framework for marginal zero-inflated models where the latent distribution is a member of the exponential dispersion family, focusing on common distributions for count data. In particular, our discussion includes the marginal zero-inflated binomial (MZIB) model, which has not been discussed previously. The details of maximum likelihood estimation via the EM algorithm are presented and the properties of the estimators as well as Wald and likelihood ratio-based inference are examined via simulation. Two examples presented illustrate the advantages of MZIP, MZINB, and MZIB models for practical data analysis.     

Statistical methodology for assessing homology of intronic regions of genes

We consider the problem of statistically evaluating the similarity of DNA intronic regions of genes. Present algorithms are based on matching a sequence of interest with known DNA sequences in a gene bank and are designed primarily to assess homology among exonic regions of genes. Most research focuses on exonic regions because they have a clear biological significance, coding for proteins, and therefore tend to be more conserved in evolution than intronic regions. To investigate whether the intronic features of genes whose expression is highly sensitive to environmental perturbations differ from genes that have a more constant expression, a collection of oncogenes, tumor suppressor genes, and nonregulatory genes involved in energy metabolism are compared. An analysis of the features of these genes' intronic regions result in clustering by regulatory group. In addition, Billingsley's test for Markov structure (1961) suggests that 67% of the intronic regions in this collection of genes show evidence of nonrandom structure, indicating the possibility of a biological function for these regions. The result of Billingsley's test for homology is used as input to a clustering algorithm. The biological significance of this methodology lies in the identification of groups based on the intronic regions from genes of unknown function. With the advent of rapid sequencing techniques, there is a great need for statistical techniques to help identify the purpose of poorly understood portions of genes. These methods can be utilized to assess the functional group to which such a gene might possibly belong.     

Estimating the prevalence of adolescent gambling disorders: A quantitative synthesis and guide toward standard gambling nomenclature

This article reviews the extant published and unpublished studies that estimate the prevalence of adolescent gambling problems in North America. The nine nonduplicative studies identified by our literature search included data collected from more than 7700 adolescents from five different regions of the United States and Canada. In addition to comparing the conceptual and methodological differences that exist among these studies, this article employed a meta-analytic strategy to synthesize prevalence estimates from the existing studies. This analysis revealed that within a 95 percent confidence interval, between 9.9% and 14.2% of adolescents are at risk of developing or returning to serious gambling problems. Similarly, between 4.4% and 7.4% of adolescents exhibit seriously adverse compulsive or pathological patterns of gambling activity. Finally, the discussion proposes a generic multi-level classification scheme to reconcile the divergent classification methods and data reporting strategies. This new multi-level approach to reporting gambling prevalence will facilitate interstudy comparisons among existing estimates of gambling prevalence and help to provide a general data reporting system for future research.     

如何发明

深圳长期以来被称作是全球制造业中心,而且它已经得到了联合国教科文组织"设计之都"的称号,我想深圳的下一个目标就是建立一个"创新之都".不知道我是否有资格在这里建议深圳这样一个大城市怎样更具创意,如果要我提建议的话,我会让大家考虑一些边界模糊的设计,把一些不寻常的东西结合起来,尽量保持多学科的融合,因为创新来自予内部.     

Meta-Power,Social Organization,and the Shaping of Social Action

Interactionist analyses of social organization stimulate examination of how social situations and collective activity are shaped. Meta-power, the creation and control of distal situations, and organization as a structuration of meta-power are used as tools for exploring the shaping of situations. Five meta-power processes are presented: strategic agency, rules and conventions, structuring situations, culture construction, and empowering delegates. These processes illustrate how situations are created or altered. This paper offers a view of social organization that emphasizes relations among situations, linkages between consequences and conditions, and networks of collective activity across space and time. The conclusion calls for additional research to make more explicit the nature of social organization and its social conditions.     

“Facing” leaders: Facial expression and leadership perception

This experimental study investigated the effect of a leader's expression of happy versus nervous emotions on subsequent perceptions of leadership and ratings of traits associated with implicit leadership theories (ILTs). Being fast and universally understood, emotions are ideal stimuli for investigating the dynamic effects of ILTs, which were understood in this study in terms of the constraints that expressed emotions impose on the connectionist networks that activate ILTs. The experimental design contrasted videotaped and still frame presentations of a leadership event; however, this methodological factor had no significant effects and analyses were thus collapsed across this factor. Key findings were that the expression of a happy versus nervous emotion at the end of a problem-solving sequence had multiple effects: happy emotions resulted in higher leadership ratings, higher trait ratings, greater correlations among trait ratings, and greater dependence of trait ratings on leadership perceptions. An exploratory model suggested that leadership impressions mediated the effects of facial emotions on trait ratings. The discussion further links the study findings with interpretations in terms of ILTs and many types of constraints on these cognitive structures. It also suggests ways to integrate these ideas with advances in neuroscience research.     

Dynamic Pricing to Minimize Maximum Regret

We consider a dynamic pricing problem that involves selling a given inventory of a single product over a short, two‐period selling season. There is insufficient time to replenish inventory during this season, hence sales are made entirely from inventory. The demand for the product is a stochastic, nonincreasing function of price. We assume interval uncertainty for demand, that is, knowledge of upper and lower bounds but not a probability distribution, with no correlation between the two periods. We minimize the maximum total regret over the two periods that results from the pricing decisions. We consider a dynamic model where the decision maker chooses the price for each period contingent on the remaining inventory at the beginning of the period, and a static model where the decision maker chooses the prices for both periods at the beginning of the first period. Both models can be solved by a polynomial time algorithm that solves systems of linear inequalities. Our computational study demonstrates that the prices generated by both our models are insensitive to errors in estimating the demand intervals. Our dynamic model outperforms our static model and two classical approaches that do not use demand probability distributions, when evaluated by maximum regret, average relative regret, variability, and risk measures. Further, our dynamic model generates a total expected revenue which closely approximates that of a maximum expected revenue approach which requires demand probability distributions.