Studies on statistical analysis process of lifetime information

本项目的目的是开发统计工具和方法，用于分析医疗领域的数据，特别是用于分析寿命（生存时间或失效时间）数据及其相关领域。如果把寿命理解为某个事件发生的时间，那么在可靠性、教育、心理学、测试理论、统计金融等许多领域都可能有相同结构的数据，因此寿命分析方法有着广泛的相关领域。寿命数据是通过观察包括人、动物、鱼类等在内的每一种生物而获得的，由于其种类繁多，因此数据分布广泛且存在偏差。因此，它是非常困难的应用经典的参数程序，其中的正态性的误差分布，线性的平均结构和均匀性的误差方差的假设。因此，我们的注意力集中在非参数方法，半参数方法，稳健统计和统计 ...更多信息 卡尔图形公司。调查主任和调查员学习了上述程序的统计理论、方法和应用。特别是，我们发表了论文，并在几个研究会议上介绍了（1）纵向数据的方差分析方法，（2）基于深度概念的鲁棒估计，（3）AIC小波基函数的决策，（4）样条平滑方差齐性的诊断，（5）决策树回归模型的构建，（6）研究幂变换的性质，这些幂变换被提出来获得正态性、线性和方差齐性，（7）估计因果效应，（8）发展计算机密集型方法来分析过度分散的分类数据，（9）上述程序的应用。此外，我们还举行了五次科学会议。我们有许多参与者，包括私营企业的数据分析师。我们进行了令人兴奋的讨论，对研究工作者和数据分析师都很有用。少

The purpose of this project is to develop statistical tools and methods which are useful to analyze data given in the medical fields, especially, useful to analyze lifetime (survival time or failure time) data and its related fields. If we interpret the lifetime as the time certain event occurs, then we may have data with the same structure in many fields of Reliability, Education, Psychology, Test Theory, Statistical Finance and so on. Hence the methods of lifetime analysis have enormous related fields. Lifetime data is taken by observing every living thing including human beings, animals, fishes and sso on, and due to their large variety the data is widely spread and skewed. Hence it is very difficult to apply classical parametric procedures where the normality of error distribution, the linearity of the mean structure and the homogeneity of error variance are assumed. Thus our attentions are focused on nonparametric procedures, semi-parametric methods, robust statistics and statisti … More cal graphics. Most of them are computer intensive methods.Head investigator and investigators studied statistical theory, methods and applications of the above procedures. Especially, we published papers and presented at several research meetings on (1)analysis of variance method for longitudinal data, (2)robust estimator based on the notion of depth, (3)decision of Wavelet bases functions by AIC, (4)diagnosis of the homogeneity of variances by spline smoothing, (5)construction of regression models by decision trees, (6)investigation of the properties of power transformations which are proposed to get normality, linearity and homogeneity of variances, (7)estimation of the causal effects, (8)developing computer intensive methods to analyze over-dispersed categorical data, (9)applications of the above procedures.Furthermore, we had scientific meetings five times. We had many participants including data analysts of private enterprizes. And we had exciting discussion useful both for research workers and data analysts. Less