A multiple imputation method for incomplete correlated ordinal data using multivariate probit models

The multiple imputation technique has proven to be a useful tool in missing data analysis. We propose a Markov chain Monte Carlo method to conduct multiple imputation for incomplete correlated ordinal data using the multivariate probit model. We conduct a thorough simulation study to compare the performance of our proposed method with two available imputation methods – multivariate normal-based and chain equation methods for various missing data scenarios. For illustration, we present an application using the data from the smoking cessation treatment study for low-income community corrections smokers.     

Demographic Changes in East Malaysia and their Relationship with those in the Peninsula 1960–80

Hardly anything is known about the demography of East Malaysia, that is of the lesser developed regions of Sabah and Sarawak, because of the wide range of deficiencies in the available data. This paper uses a range of indirect methods to construct a demographic profile of Sabah and Sarawak over the period 1960 to 1980. Comparisons are made between these areas and Peninsular Malaysia and some overall Malaysian estimates are given. The study suggests that between 1965 and 1980 there were large gains in life expectancy among the indigenous communities in Sabah and Sarawak, although their life expectancies are still shorter than those of the Chinese. Differentials in life chances between these regions and Peninsular Malaysia narrowed appreciably during the 1970s. Over the same period there were falls in levels of fertility. These were most spectacular among the Chinese communities and the groups living in and around the urban areas in Sarawak. There has been some decline in fertility among the indigenous groups in Sabah but current levels remain higher than among the indigenous groups in Sarawak and the Malays in the Peninsula.     

Empirical and simulated adjustments of composite likelihood ratio statistics

Composite likelihood inference has gained much popularity thanks to its computational manageability and its theoretical properties. Unfortunately, performing composite likelihood ratio tests is inconvenient because of their awkward asymptotic distribution. There are many proposals for adjusting composite likelihood ratio tests in order to recover an asymptotic chi-square distribution, but they all depend on the sensitivity and variability matrices. The same is true for Wald-type and score-type counterparts. In realistic applications, sensitivity and variability matrices usually need to be estimated, but there are no comparisons of the performance of composite likelihood-based statistics in such an instance. A comparison of the accuracy of inference based on the statistics considering two methods typically employed for estimation of sensitivity and variability matrices, namely an empirical method that exploits independent observations, and Monte Carlo simulation, is performed. The results in two examples involving the pairwise likelihood show that a very large number of independent observations should be available in order to obtain accurate coverages using empirical estimation, while limited simulation from the full model provides accurate results regardless of the availability of independent observations. This suggests the latter as a default choice, whenever simulation from the model is possible.     

经济发展与村民投票参与 ——来自民政部全国抽样调查的证据

基于民政部全国村民自治抽样调查数据,实证分析了经济发展对我国村民在村委会选举中投票参与的影响,得到如下主要结论:第一,家庭在村中的相对经济地位越高、内部政治效能越强,村民越会参与投票;除了初中文化水平的村民投票概率高些之外,小学以下、小学、初中以上文化水平的村民在投票参与概率上无差别。第二,家庭经济地位、受教育程度对投票概率的影响随着村整体经济发展水平变化。第三,家庭经济地位、教育对投票参与的影响存在性别差异。第四,基层政府选举干预不仅降低村的整体投票率,而且还使得家庭经济地位、内部政治效能对个人投票概率的积极影响不复存在,但却提高了高文化水平村民的投票概率。     

城镇污水、垃圾处理收费制度改革中微观主体的行为研究——基于order probit模型对居民缴费意愿的分析

微观主体的缴费意愿对污水、垃圾处理收费制度改革具有重要影响。基于调研数据，对城镇污水、垃圾处理收费制度的现状和影响因素进行了描述性分析和order probit模型的计量分析。研究发现，居民收入水平和环保宣传力度对缴费意愿具有显著的影响，而地区性因素和居民个体特征因素对缴费意愿的影响不显著，据此提出了改革收费制度、加强非正式制度建设等政策建议。     

企业财务风险预测模型实证比较分析

企业财务风险一直是风险管理理论和实务界关心的热点话题。运用判别分析和计量经济方法对重庆市某商业银行的461个样本企业2002-2005年的违约特征进行实证检验和预测。结果发现最重要的决定变量是资产负责率、酸性试验比率、资产净利率等7个财务比率以及企业所处的产业部门,考虑了异方差性的probit模型有更好的预测能力。     

欠发达地区农民工留城倾向的影响因素分析

新型城镇化的核心在于实现人的城镇化,能否增强农民工留在打工城市的意愿和能力是实现农民工市民化的关键途径之一。根据贵阳市农民工的调研数据,运用有序probit模型,实证研究了个人综合特征、家庭特征和个人满意度对农民工留在打工城市的影响。分析结果表明:家庭所在地与打工地距离越近,受教育程度较高、在城市居住时间较长,全家迁移,住房条件越好,已婚,对收入水平越满意、对工作环境越满意的农民工,越倾向于长期留在打工城市。且第一代农民工和新生代农民工的留城倾向受到不同因素的影响,表现出较强的代际差异性。     

新生代农民工住房满意度影响因素与对策研究

新生代农民工是中国城市化进程中需要面对的新群体,其住房问题是现阶段城镇住房保障领域的重要问题之一,事关中国城市化质量的提升和可持续发展.文章以重庆市为例,采用Ordered Probit模型估计重点研究了新生代农民工个体属性、职业特征与居住方式3个特征维度对新生代农民工住房满意度的影响.数据结果显示:性别、年龄、婚姻状况、是否有子女、收入水平、进城务工时间、住房面积、居住形式、住房支出、住房配套设施和职住通勤时间等因素对新生代农民工的住房满意度有显著影响.而职业类别和是否缴纳住房公积金目前对新生代农民工住房满意度的影响不够显著.文章最后提出了相应的政策建议.     

Regression Models and Risk Estimation for Mixed Discrete and Continuous Outcomes in Developmental Toxicology

Multivariate dose-response models have recently been proposed for developmental toxicity data to simultaneously model malformation incidence (a binary outcome), and reductions in fetal weight (a continuous outcome). In this and other applications, the binary outcome often represents a dichotomization of another outcome or a composite of outcomes, which facilitates analysis. For example, in Segment II developmental toxicology studies, multiple malformation types (i.e., external, visceral, skeletal) are evaluated on each fetus; malformation status may also be ordinally measured (e.g., normal, signs of variation, full malformation). A model is proposed is for fetal weight and multiple malformation variables measured on an ordinal scale, where the correlations between the outcomes and between the offspring within a litter are taken into account. Fully specifying the joint distribution of outcomes within a litter is avoided by specifying only the distribution of the multivariate outcome for each fetus and using generalized estimating equation methodology to account for correlations due to litter clustering. The correlations between the outcomes are required to characterize joint risk to the fetus, and are therefore a focus of inference. Dose-response models and their application to quantitative risk assessment are illustrated using data from a recent developmental toxicology experiment of ethylene oxide in mice.