Some large trial properties of minimum likelihood allocation

The method of minimum likelihood allocation (MLA) for allocating subjects to treatments in a clinical trial amounts to checking at each stage which allocation would lead an outside observer to find the least evidence of a relationship between treatment and factors of prognostic significance, assuming that the observer would use a linear exponential model. One advantage of MLA is that results from game theory and likelihood theory can be used to prove it has desirable long run properties. Two of these demonstrated here are (1) ‘consistency’, in the sense that the average likelihood ratio which measures design imbalance tends to zero, and (2) ‘efficiency’ in the sense that the variance estimates of treatment effects will tend to be minimized in the long run.     

LOGISTIC REGRESSION COMPARED TO NORMAL DISCRIMINATION FOR NON-NORMAL POPULATIONS'

An investigation is undertaken of the logistic regression procedure for estimating the posterior probability of an object belonging to one of two populations. The asymptotic bias and mean square error associated with the procedure are derived for univariate populations whose distributions satisfy the general Day-Kerridge model for which the logistic form is valid for the posterior probability. These properties are compared with those of the normal discrimination method based on the classical assumption of normal populations with common variances. The asymptotic relative efficiency of logistic regression is considered on the basis of asymptotic mean square error.     

新生代农民工职业培训意愿及其影响因素实证分析——基于江西省的调查

新生代农民工问题的解决是推进城乡二元体制改革、促进社会和谐稳定的一个关键性问题,而职业培训对新生代农民工提高自身素质具有不可或缺的独特作用。以江西省的调研数据为基础,利用交叉表和多元有序Logistic模型实证分析了个人因素、成本因素和收益因素对新生代农民工接受职业培训意愿的影响。结果表明,新生代农民工接受职业培训的意愿较强烈,个人因素中性别、文化程度、婚姻状况对新生代农民工职业培训意愿影响显著;成本因素中培训时间越长,新生代农民工职业培训意愿越弱;收益因素中培训对收入的影响和对职业发展的影响都与培训意愿呈显著的正相关关系。     

Liu-Type Logistic Estimator

It is known that multicollinearity inflates the variance of the maximum likelihood estimator in logistic regression. Especially, if the primary interest is in the coefficients, the impact of collinearity can be very serious. To deal with collinearity, a ridge estimator was proposed by Schaefer et al. The primary interest of this article is to introduce a Liu-type estimator that had a smaller total mean squared error (MSE) than the Schaefer's ridge estimator under certain conditions. Simulation studies were conducted that evaluated the performance of this estimator. Furthermore, the proposed estimator was applied to a real-life dataset.     

Binary Regression with Stochastic Covariates

In binary regression the risk factor X has been treated in the literature as a non-stochastic variable. In most situations, however, X is stochastic. We present solutions applicable to such situations. We show that our solutions are more precise than those obtained by treating X as non-stochastic when, in fact, it is stochastic.     

On a Class of Distributions Defined by the Relationship Between Their Density and Distribution Functions

Knowledge concerning the family of univariate continuous distributions with density function f and distribution function F defined through the relation f(x) = F ^α(x)(1 ? F(x))^β, α, β ? , is reviewed and modestly extended. Symmetry, modality, tail behavior, order statistics, shape properties based on the mode, L-moments, and—for the first time—transformations between members of the family are the general properties considered. Fully tractable special cases include all the complementary beta distributions (including uniform, power law and cosine distributions), the logistic, exponential and Pareto distributions, the Student t distribution on 2 degrees of freedom and, newly, the distribution corresponding to α = β = 5/2. The logistic distribution is central to some of the developments of the article.     

Determining Process Death Based on Censored Activity Data

This article addresses the problem of estimating the time of apparent death in a binary stochastic process. We show that, when only censored data are available, a fitted logistic regression model may estimate the time of death incorrectly. We improve this estimation by utilizing discrete-event simulation to produce simulated complete time series data. The proposed methodology may be applied to situations where time of death cannot be formally determined and has to be estimated based on prolonged inactivity. As an illustration, we use observed monthly activity patterns from 300 real Open Source Software development projects sampled from Sourceforge.net.     

“两型”社会建设中的农户土地转出意愿分析——以长沙大河西光导区为例

对长沙大河西4个典型土地流转示范村进行农户土地转出意愿问卷调查,建立Logistic回归模型,分析农户土地转出意愿及影响因素。在5％水平下。对土地转出意愿具有显著的影响因素有中介组织、就业类型、家庭总收入、土地流转合同和家庭总人口,而年龄、受教育程度和家庭参保人数等对农户土地转出意愿没有显著性影响。     

Recurrence relations for moments of progressively censored order statistics from logistic distribution with applications to inference

In this paper, we establish several recurrence relations for the single and product moments of progressively Type-II right censored order statistics from a logistic distribution. The use of these relations in a systematic manner allows us to compute all the means, variances and covariances of progressively Type-II right censored order statistics from the logistic distribution for all sample sizes n, effective sample sizes m, and all progressive censoring schemes (R₁,…,R_m). The results established here generalize the corresponding results for the usual order statistics due to [Shah, 1966] and [Shah, 1970]. These moments are then utilized to derive best linear unbiased estimators of the location and scale parameters of the logistic distribution. A comparison of these estimators with the maximum likelihood estimations is then made. The best linear unbiased predictors of censored failure times are briefly discussed. Finally, an illustrative example is presented.