Modeling Zero-Inflated and Overdispersed Count Data: An Empirical Study of School Suspensions

The purpose of this article is to develop a statistical model that best explains variability in the number of school days suspended. Number of school days suspended is a count variable that may be zero-inflated and overdispersed relative to a Poisson model. Four models were examined: Poisson, negative binomial, Poisson hurdle, and negative binomial hurdle. Additionally, the probability of a student being suspended for at least 1 day was modeled using a binomial logistic regression model. Of the count models considered, the negative binomial hurdle model had the best fit. Modeling the probability of a student being suspended for at least 1 day using a binomial logistic regression model with interactions fit both the training and test data and had adequate fit. Findings here suggest that both the negative binomial hurdle and the binomial logistic regression models should be considered when modeling school suspensions.     

分组零膨胀泊松模型的半参数统计推断

泊松回归模型常常用于计数数据的研究中,然而在实际数据中零值的比例可能远远大于泊松分布中取零值的概率,而且这些零值通常都有其特殊含义.此外计数数据可能是分组数据,即观测到的数据不是确切值而只是已知其落在某一个区间范围之内;或者某些特定的数据,例如工资,要先对它进行人为的分组然后再进行分析.考虑一种零膨胀泊松半参数回归模型来处理上述分组计数数据.该模型中泊松分布的期望与协变量之间采用部分线性连接函数,而零值的概率与协变量之间采用线性连接函数.利用Sieve极大似然估计方法来估计该回归模型中参数和非参数函数,并提出了一种得分检验方法来检验是否存在零膨胀.在一定正则条件下,获得了Sieve极大似然估计的渐近性质,证明了参数部分的估计是强相合,渐近正态及渐近有效的;同时非参数函数的估计达到了最优收敛速度.模拟研究表明,估计和检验方法效果都比较好,最后将此模型和推断方法应用于一组公共卫生领域实际数据研究.     

两类零膨胀负二项回归模型在汽车保险定价中的应用

讨论了两种分布形式的零膨胀负二项回归模型,并应用一组实际汽车保险损失数据对两类模型进行了实证比较．结果表明,对于具有零膨胀特征的损失数据,零膨胀负二项回归模型的拟合结果优于普通索赔频率回归模型．     

Longitudinal Models for Ordinal Data With Many Zeros and Varying Numbers of Response Categories

Ordinal response scales are often used to survey behaviors, including data collected in longitudinal studies. Advanced analytic methods are now widely available for longitudinal data. This study evaluates the performance of 4 methods as applied to ordinal measures that differ by the number of response categories and that include many zeros. The methods considered are hierarchical linear models (HLMs), growth mixture mixed models (GMMMs), latent class growth analysis (LCGA), and 2-part latent growth models (2PLGMs). The methods are evaluated by applying each to empirical response data in which the number of response categories is varied. The methods are applied to each outcome variable, first treating the outcome as continuous and then as ordinal, to compare the performance of the methods given both a different number of response categories and treatment of the variables as continuous versus ordinal. We conclude that although the 2PLGM might be preferred, no method might be ideal.     

The correlates of sports participation in Europe

Abstract

Based on the Eurobarometer data from 2009 (N = 26,788), this paper investigates the correlates of sports participation. In addition to examining standard socio-demographic, economic and lifestyle factors, the paper also focuses on the impact of motivational factors, the availability of sports infrastructure and government support, for the first time collectively at the European level. A further contribution of the paper is that it simultaneously investigates both the decision to participate in sport and the frequency of sports participation in this context. This is made possible through the application of a Zero-Inflated Ordered Probit estimator. This estimator also takes into account two types of non-participants: those who have never participated in sport and those who did not participate at the time of the survey. The results show that the decision to participate in sports and the frequency of sports participation of males and females are affected by different factors, therefore distinct government policies should be applied to attract new, and retain the existing, participants. For example, women are affected more by a need to improve self-esteem, while the men to produce social integration. The provision of sports facilities is of more importance for males, which may indicate a male-oriented nature of the sports facilities, for example, the gym. However, the number of adults and the number of children in the household reduce the probability of sports participation by females. Therefore, higher provision of childcare may be important if female participation is to be increased.     

中国创新合作网络的演进特征及影响因素研究——以SCI论文合作为例

创新驱动战略实施背景下,融入创新合作网络是中国各省域提升区域创新能力的重要途径。本文基于2008—2018年中国省际之间在Web of Science核心合集发表的论文合作数,构建中国省际创新合作网络,描绘其时空演化特征,并借助零膨胀负二项回归深入分析影响机制。研究发现：中国省际创新合作网络结构逐渐复杂化、均衡化,省际创新合作网络中网络节点之间的联系不断丰富,在网络中重要节点省份逐渐增多,而且随着时间推移,网络结构不断优化。多维邻近性检验显示网络邻近性、产业邻近性是影响创新合作关系的重要因素,地理邻近性、经济邻近性影响较小,网络邻近性可以通过调节地理邻近性、经济邻近性影响创新合作。     

分组零膨胀泊松模型的半参数统计推断

泊松回归模型常常用于计数数据的研究中,然而在实际数据中零值的比例可能远远大于泊松分布中取零值的概率,而且这些零值通常都有其特殊含义.此外计数数据可能是分组数据,即观测到的数据不是确切值而只是已知其落在某一个区间范围之内;或者某些特定的数据,例如工资,要先对它进行人为的分组然后再进行分析.考虑一种零膨胀泊松半参数回归模型来处理上述分组计数数据.该模型中泊松分布的期望与协变量之间采用部分线性连接函数,而零值的概率与协变量之间采用线性连接函数.利用Sieve极大似然估计方法来估计该回归模型中参数和非参数函数,并提出了一种得分检验方法来检验是否存在零膨胀.在一定正则条件下,获得了Sieve极大似然估计的渐近性质,证明了参数部分的估计是强相合,渐近正态及渐近有效的;同时非参数函数的估计达到了最优收敛速度.模拟研究表明,估计和检验方法效果都比较好,最后将此模型和推断方法应用于一组公共卫生领域实际数据研究.     

专利知识吸收和扩散演化规律及影响研究

    分析中国医药领域专利知识吸收和扩散演化规律及知识吸收对知识扩散影响,有助于快速选择并吸收相关资源,为加大基础研究投入强度提供数据支撑,为科技资源整合策略提供支持。本文以2000—2014年美国专利商标局收录的中国医药领域2326件专利及其引用的43 822篇专利文献、35 573篇论文文献为研究对象,从专利知识吸收及知识扩散两个角度出发,采用多元方差分析、零膨胀负二项回归及多元线性回归进行多维度分析。结果表明：专利知识吸收逐年增加,但知识扩散并未形成稳定趋势;不同时间段内知识吸收及扩散各测度指标显著不同;专利文献知识吸收数量、质量及论文文献知识吸收质量均对专利知识扩散产生负向影响;吸收论文知识构件对专利知识扩散产生正向影响;吸收论文数量与知识扩散广度、强度负相关;吸收专利知识构件与知识扩散广度正相关,但与知识扩散强度与速度均无相关关系;专利及论文文献知识吸收新颖性对知识扩散广度、强度及速度均无影响。