Multiple paths in educational transitions: A multinomial transition model with unobserved heterogeneity

In many countries educational branching points consist of more than two qualitatively different alternatives, and only some alternatives provide the opportunity of continuing into higher education. I develop a multinomial transition model for modeling the effects of family background characteristics and individual characteristics on these complex educational careers. The model controls for unobserved heterogeneity that may, if ignored, result in biased estimates. Compared to previous research, I explicitly include instrumental variables that ensure identification of the unobserved component. I apply the model to the Danish case and analyze data which covers the educational careers of a cohort of Danes born around 1954. I find that the model brings forward non-trivial heterogeneity in the influence of family background and ability on qualitatively different choice alternatives both within and across transitions. I also find that not controlling for unobserved heterogeneity leads to marked underestimation of the family background effect on both early and late transitions in the educational career.     

Tests for the equality of multinomial parameters

In this paper we face the problem of testing the equality of two or more parameters of a multinomial distribution. We develop a likelihood ratio test and we consider an asymptotically equivalent Pearson's statistic. Moreover we develop an exact and a randomized test. Relationships between these tests are then discussed. The behaviour of these tests is studied by simulations. Results from two known tests developed for less general situations are compared to ours.     

Stylometric analyses using Dirichlet process mixture models

Stylometry refers to the statistical analysis of literary style of authors based on the characteristics of expression in their writings. We propose an approach to stylometry based on a Bayesian Dirichlet process mixture model using multinomial word frequency data. The parameters of the multinomial distribution of word frequency data are the “word prints” of the author. Our approach is based on model-based clustering of the vectors of probability values of the multinomial distribution. The resultant clusters identify different writing styles that assist in author attribution for disputed works in a corpus. As a test case, the methodology is applied to the problem of authorship attribution involving the Federalist papers. Our results are consistent with previous stylometric analyses of these papers.     

安徽省农业经营主体的影响因素及其地区差异研究

基于安徽省新型农业经营主体发展的概况分析,从微观角度利用家计调查数据实证分析农业经营主体的影响因素及其地区差异。结果表明:个人因素、家庭负担率、现有土地面积正向影响农业经营主体;而食品支出比重、非农因素负向影响农业经营主体,土地流转意愿对农业经营主体的影响有所差异;皖南、江淮地区和皖北的农业经营主体影响因素之间存在差异。基于此,提出提高农民农业生产技术水平和非农技能、政府建立有效的土地流转平台、因地制宜发展农业经营主体等建议。     

基层农技员推广行为与推广绩效的实证研究——基于农户视角的调查

基于农户的视角获取基层农技员的推广行为,从农户水稻产量、种稻知识技能提高以及推广服务满意度三个层面界定推广绩效,并实证分析基层农技员推广行为对推广绩效的影响。研究表明,基层农技员推广行为综合得分越高对于农户水稻产量增加、种稻知识技能提高以及农技服务满意度评价都有显著的正向影响。     

A Clustering Method for Categorical Ordinal Data

Often, categorical ordinal data are clustered using a well-defined similarity measure for this kind of data and then using a clustering algorithm not specifically developed for them. The aim of this article is to introduce a new clustering method suitably planned for ordinal data. Objects are grouped using a multinomial model, a cluster tree and a pruning strategy. Two types of pruning are analyzed through simulations. The proposed method allows to overcome two typical problems of cluster analysis: the choice of the number of groups and the scale invariance.     

Locally D-Optimal Design for a Logit Model in Discrete Choice Experiment

Conjoint analysis is concerned with understanding how people make choice between products or services (alternatives) or a combination of product and service (choice set), so that businesses can design new products or services that better meet customers needs. In this situation, logit model (Multinomial Logit Model) has been used to calculate the probability related to choosing an alternative in a choice set with the highest utility. Then I considered several choice sets instead of one. In this article, I have used the locally D-optimal design for the combination of the level of attributes (two attributes each with two levels) to create alternatives. The optimal combination of alternatives in choice sets which help us to have a suitable choice.     

Zur bestimmung von bayes-lösungen bei messender prüfung

A model of sampling inspection by variables is presented, where the loss function and the a priori distribution of the unknown defective fraction are assumed to be known. The existence of a BAYES rule in the class of relevant decision functions (sampling plans) is proved. Furthermore, it is shown that under certain conditions the decision functions "accept without sampling" or "reject without sampling" are BAYESian decision rules. Some numerical examples are presented to illustrate the theory developed in the paper.     

Bayesian and Classical Approaches for Hypotheses Testing in Trisomies

We introduce classical approaches for testing hypotheses on the meiosis I non disjunction fraction in trisomies, such as the likelihood-ratio, bootstrap, and Monte Carlo procedures. To calculate the p-values for the bootstrap and Monte Carlo procedures, different transformations in the data are considered. Bootstrap confidence intervals are also used as a tool to perform hypotheses tests. A Monte Carlo study is carried out to compare the proposed test procedures with two Bayesian ones: Jeffreys and Pereira-Stern tests. The results show that the likelihood-ratio and the Bayesian tests present the best performance. Down syndrome data are analyzed to illustrate the procedures.     

Conditioning out rare events for exponential families has negligible effect on inference

ABSTRACT

Suppose that we observe X ～Binomial(n, p). Inference on p is difficult if X = 0 or n. One way around this is to condition on these events not happening. We show that this has only an exponentially small effect on its cumulants. This is also true if we condition away other rare events. Our results are presented for exponential families, with applications to the binomial, multinomial and negative multinomial distributions.