Confidence Intervals for Variance Components in Measurement System Capability Studies

In Measurement System Analysis a relevant issue is how to find confidence intervals for the parameters used to evaluate the capability of a gauge. In literature approximate solutions are available but they produce so wide intervals that they are often not effective in the decision process. In this article we introduce a new approach and, with particular reference to the parameter γ_R, i.e., the ratio of the variance due to the process and the variance due to the instrument, we show that, under quite realistic assumptions, we obtain confidence intervals narrower than other methods. An application to a real microelectronic case study is reported.     

Bias corrected estimation for generalized probit regression with covariate measurement error and censored responses

In this paper, we propose a bias corrected estimate of the regression coefficient for the generalized probit regression model when the covariates are subject to measurement error and the responses are subject to interval censoring. The main improvement of our method is that it reduces most of the bias that the naive estimates have. The great advantage of our method is that it is baseline and censoring distribution free, in a sense that the investigator does not need to calculate the baseline or the censoring distribution to obtain the estimator of the regression coefficient, an important property of Cox regression model. A sandwich estimator for the variance is also proposed. Our procedure can be generalized to general measurement error distribution as long as the first four moments of the measurement error are known. The results of extensive simulations show that our approach is very effective in eliminating the bias when the measurement error is not too large relative to the error term of the regression model.     

A new absolute continuous bivariate generalized exponential distribution

The generalized exponential is the most commonly used distribution for analyzing lifetime data. This distribution has several desirable properties and it can be used quite effectively to analyse several skewed life time data. The main aim of this paper is to introduce absolutely continuous bivariate generalized exponential distribution using the method of Block and Basu (1974). In fact, the Block and Basu exponential distribution will be extended to the generalized exponential distribution. We call the new proposed model as the Block and Basu bivariate generalized exponential distribution, then, discuss its different properties. In this case the joint probability distribution function and the joint cumulative distribution function can be expressed in compact forms. The model has four unknown parameters and the maximum likelihood estimators cannot be obtained in explicit form. To compute the maximum likelihood estimators directly, one needs to solve a four dimensional optimization problem. The EM algorithm has been proposed to compute the maximum likelihood estimations of the unknown parameters. One data analysis is provided for illustrative purposes. Finally, we propose some generalizations of the proposed model and compare their models with each other.     

Simultaneous confidence bands for nonlinear regression models

The maximization and minimization procedure for constructing confidence bands about general regression models is explained. Then, using an existing confidence region about the parameters of a nonlinear regression model and the maximization and minimization procedure, a generally conservative simultaneous confidence band is constructed about the model. Two examples are given, and some problems with the procedure are discussed     

家庭背景对大学生毕业去向的影响

家庭背景在高校毕业生就业中扮演的角色引起越来越多的社会关注.文章采用多元选择模型研究了家庭背景对大学生毕业去向的影响.研究发现,家庭背景对大学生毕业去向的影响显著,对毕业生在何种类型单位就业起到关键作用,学习成绩、社会工作经历的影响则不显著.在其他条件相同的情况下,拥有更好的家庭背景的高校毕业生出国、体制内就业的可能性更大,而家庭背景较差的毕业生则更可能去往三资(中外合资企业、中外合作企业、外方独资企业)企业.     

中国证券市场审计意见的决定因素

在研究可能影响审计意见因素的基础上,依据中国大陆金融市场资料库数据,运用logistic回归模型,检验了中国证券市场上影响审计意见的因素。结果表明公司的财务状况会显著影响到其所收到的审计类型,公司上市年限和年度报告的披露日期也会影响到公司的审计意见。     

On some aspects of a general class of Yule distribution and its applications

Abstract

A wide class of Yule distribution is introduced here as a generalization of the extended Yule distribution of Martinez-Rodríguez et al. and the generalized Yule distribution of Mishra and investigate some of its properties. Various methods of estimation are employed for estimating the parameters of the distribution and generalized likelihood ratio test procedures are suggested for testing the significance of the parameters of the distribution. All these procedures are illustrated with the help of real data sets.     

A simulation study of estimators for generalized linear measurement error models

The purpose of this paper is to examine the properties of several bias-corrected estimators for generalized linear measurement error models, along with the naive estimator, in some special settings. In particular, we consider logistic regression, poisson regression and exponential-gamma models where the covariates are subject to measurement error. Monte Carlo experiments are conducted to compare the relative performance of the estimators in terms of several criteria. The results indicate that the naive estimator of slope is biased towards zero by a factor increasing with the magnitude of slope and measurement error as well as the sample size. It is found that none of the biased-corrected estimators always outperforms the others, and that their small sample properties typically depend on the underlying model assumptions.     

Graphical data modeling methods using ceres plots

Identification of curvature in regression models is an important aspect of data analysis. Partial residual plots have played a major role. Recently, Cook developed a new class of plots, called CERES plots, that includes partial residual plots. Implementation of these plots necessitates modeling the relationships between certain covariates. If these relationships are linear, a partial residual plot is obtained. However, if the relationships are nonlinear, the more general CERES plot is obtained. Here, we describe an implementation of interactive methods which construct CERES plots.0     

C55. Quick and accurate rule of thumb for determining the critical value of the coefficient of correlation

Life table analysis techniques in epidemiology depend upon the asymptotic properties of the statistical test methods employed. In some instances, the statistical procedures indicate highly significant results which are, in reality, unjustified. The phenomenon may occur when the asymptotic methods are applied in situations where the cases of interest are few in number. This situation is illustrated by the 20 multiple myeloma deaths observed in the RERF Life Span Study cohort. A permutation test is applied to the life table data, although the test requires the false assumption that the censoring distribution is independent of the radiation dose. A simulation test is developed which does not require equal censoring, which has the same asymptotics as the usual test methods, and which is less likely to overestimate significance in small samples. It is found that both of these small-sample tests provide reasonable numerical solutions. In addition, the simulation test is recommended in general for analyzing life table data with unequal censoring. Finally, by using the small-sample tests, the frequency of death from multiple myeloma is shown to be positively associated with radiation dose (P<0.01).