Multivariate tests comparing binomial probabilities, with application to safety studies for drugs

Summary.  In magazine advertisements for new drugs, it is common to see summary tables that compare the relative frequency of several side-effects for the drug and for a placebo, based on results from placebo-controlled clinical trials. The paper summarizes ways to conduct a global test of equality of the population proportions for the drug and the vector of population proportions for the placebo. For multivariate normal responses, the Hotelling T ²-test is a well-known method for testing equality of a vector of means for two independent samples. The tests in the paper are analogues of this test for vectors of binary responses. The likelihood ratio tests can be computationally intensive or have poor asymptotic performance. Simple quadratic forms comparing the two vectors provide alternative tests. Much better performance results from using a score-type version with a null-estimated covariance matrix than from the sample covariance matrix that applies with an ordinary Wald test. For either type of statistic, asymptotic inference is often inadequate, so we also present alternative, exact permutation tests. Follow-up inferences are also discussed, and our methods are applied to safety data from a phase II clinical trial.     

Discrete regularized discriminant analysis

A method of regularized discriminant analysis for discrete data, denoted DRDA, is proposed. This method is related to the regularized discriminant analysis conceived by Friedman (1989) in a Gaussian framework for continuous data. Here, we are concerned with discrete data and consider the classification problem using the multionomial distribution. DRDA has been conceived in the small-sample, high-dimensional setting. This method has a median position between multinomial discrimination, the first-order independence model and kernel discrimination. DRDA is characterized by two parameters, the values of which are calculated by minimizing a sample-based estimate of future misclassification risk by cross-validation. The first parameter is acomplexity parameter which provides class-conditional probabilities as a convex combination of those derived from the full multinomial model and the first-order independence model. The second parameter is asmoothing parameter associated with the discrete kernel of Aitchison and Aitken (1976). The optimal complexity parameter is calculated first, then, holding this parameter fixed, the optimal smoothing parameter is determined. A modified approach, in which the smoothing parameter is chosen first, is discussed. The efficiency of the method is examined with other classical methods through application to data.     

Analyzing event stream dynamics in two-mode networks: An exploratory analysis of private communication in a question and answer community

Information about social networks can often be collected as event stream data. However, most methods in social network analysis are defined for static network snapshots or for panel data. We propose an actor oriented Markov process framework to analyze the structural dynamics in event streams. Estimated parameters are similar to what is known from exponential random graph models or stochastic actor oriented models as implemented in SIENA. We apply the methodology on a question and answer web community and show how the relevance of different kinds of one- and two-mode network structures can be tested using a new software.     

Life Satisfaction and Happiness in Turkey

This research aims to investigate life satisfaction and happiness in Turkey. It extends the previous researches on subjective well-being (SWB) for Turkey by considering both happiness and life satisfaction. The previous researches for Turkey are local studies, and their findings cannot be generalized to the population of Turkish society. Given these facts, the factors that shape individual happiness and life satisfaction amongst Turkish people are determined using a representative survey of sociocultural and political change, World Values Survey (WVS). Some results obtained in this study are similar to typical findings such as a negative age effect, positive influences of income and health status, and a negative effect of unemployment. Contrary to the expectations, middle education has a negative direct effect on life satisfaction among females, and the upper education level is insignificant in the life satisfaction model. By comparing the correlates of happiness and life satisfaction across different years, this research aims to provide insights for policy makers and professionals to improve the perceived lives of Turkish people.

Pooling choices or categories in multinomial logit models

The estimation of multinomial logit models today is routine. With this increased use has also come a need for testing. A test to determine whether choices can be combined is important. This paper presents a likelihood ratio test for combining choices in multinomial logit models. The use of the test is demonstrated with a simple example.     

我国居民医疗资源利用状况的不平等

医疗资源利用状况的不平等,是指不同收入组的居民在利用医疗资源方面存在显著的差异。根据2004年的中国营养与健康调查(CHNS)数据,用多元logit模型估计出我国居民医疗支出的价格弹性和收入弹性,结果表明:低收入的居民偏向于到基础医院就诊,高收入的居民偏向于到高级医院就诊;与高收入的居民相比,低收入居民受到的收入约束更大,特别是在患重病的时候,低收入居民的医疗费用更高,经济负担更重。     

试析人工神经网络运用于社会统计分析中的可能性

社会统计分析是社会研究方法中十分重要的一部分,因为定量研究所得的原始资料在经过审核、整理与汇总之后,需要进行科学系统的统计分析,才能揭示出研究资料所包含的众多信息,从而得出研究的结论。在多元统计分析方法中,研究者用得比较多的是多元线性回归分析、方差分析、log线性模型、probit模型及logistic回归分析,这些分析方法能够帮助我们对数据进行简化、对变量之间的相互依赖关系进行分析,以及根据模型进行预测。但上述方法也存在着一定的使用局限性,比如,方差分析法要假定进行均值比较的总体具有相同的方差和服从正态分布,如果不符合…     

Risk Aversion in Travel Mode Choice with Rank-Dependent Utility

Using 2004 stated preference data on travel mode collected in the Zürich area, different parametric specifications of the rank-dependent utility function in a logit mixture model show that commuters are weakly averse to small-time losses. The results also justify Yaari's dual theory of choice under risk, that the utility function is linear on outcomes but that the perception of corresponding probabilities is biased. For leisure travel, the travelers are risk neutral to small losses of time.     

Sibling death clustering in India: state dependence versus unobserved heterogeneity

Summary.  Data from a range of environments indicate that the incidence of death is not randomly distributed across families but, rather, that there is a clustering of death among siblings. A natural explanation of this would be that there are (observed or unobserved) differences across families, e.g. in genetic frailty, education or living standards. Another hypothesis that is of considerable interest for both theory and policy is that there is a causal process whereby the death of a child influences the risk of death of the succeeding child in the family. Drawing language from the literature on the economics of unemployment, the causal effect is referred to here as state dependence (or scarring). The paper investigates the extent of state dependence in India, distinguishing this from family level risk factors that are common to siblings. It offers some methodological innovations on previous research. Estimates are obtained for each of three Indian states, which exhibit dramatic differences in socio-economic and demographic variables. The results suggest a significant degree of state dependence in each of the three regions. Eliminating scarring, it is estimated, would reduce the incidence of infant mortality (among children who are born after the first child) by 9.8% in the state of Uttar Pradesh, 6.0% in West Bengal and 5.9% in Kerala.     

Necessary sample sizes for categorial data

This paper deals with the problem how to determine the necessary sample size for the estimation of the parameter π=(π1,...,πk) (πj ≥ 0, Σjπj=1) based on the vector f=(f1,...,fk) of relative frequencies with sample size n. The vector n-f has a multinomial distribution. For a given precision c, 0≤c≤1, and a given confidence number β, 0≤β≤1, there exists a smallest positive integer N⁰=N⁰(β, c, k) with P{|fj−πj|≤c; j=1, ...,k}≥β for all sample sizes n≥N⁰ and for all π. As results are given in this paper exact upper bounds for N⁰ and an improved asymptotical upper bound for N⁰ which is derived from the asymptotical multinormal approximation for the distribution of f.