On Use of Distinct Respondents in Randomized Response Surveys

It is well known for direct response surveys (DR), where the responses are obtained from the respondents directly, that the sample mean, based on distinct units of a simple random sample selected with replacement (SRSWR) method, is more efficient than the sample mean based on all the units including repetition. In this paper, it is shown that a linear unbiased estimator based on distinct units is inadmissible for estimating a finite population mean when the sample is selected by an arbitrary with replacement (WR) sampling scheme and the responses are obtained independently by some RR technique. Efficiencies for a few linear unbiased estimators are compared under SRSWR sampling.     

On a Mixed-Type Randomized Rule for Selecting Superior Binomial Models

We propose a new class of selection rules for selecting superior models from finite Binomial models. This new class of rules extends the classes of classical rules and shows its superiority to the classical selection rules by some Monte Carlo results. This new class of rules is easier and more flexible to apply than these known classical rules.     

A Generalized Logistic Model for Quantal Response Bioassay

In bioassay, where different levels of the stimulus may represent different doses of a drug, the binary response is the death or survival of an individual receiving a specified dose. In such applications, it is common to model the probability of a positive response P at the stimulus level x by P = F(x′β), where F is a cumulative distribution function and β is a vector of unknown parameters which characterize the response function. The two most popular models used for modelling binary response bioassay involve the probit model [BLISS (1935), FINNEY (1978)], and the logistic model [BERKSON (1944), BROWN (1982)]. However, these models have some limitations. The use of the probit model involves the inverse of the standard normal distribution function, making it rather intractable. The logistic model has a simple form and a closed expression for the inverse distribution function, however, neither the logistic nor the probit can provide a good fit to response functions which are not symmetric or are symmetric but have a steeper or gentler incline in the central probability region. In this paper we introduce a more realistic model for the analysis of quantal response bioassay. The proposed model, which we refer to it as the generalized logistic model, is a family of response curves indexed by shape parameters m₁ and m₂. This family is rich enough to include the probit and logistic models as well as many others as special cases or limiting distributions. In particular, we consider the generalized logistic three parameter model where we assume that m₁ = m, m is a positive real number, and m₂ = 1. We apply this model to various sets of data, comparing the fit results to those obtained previously by other dose-response curves such as the logistic and probit, and showing that the fit can be improved by using the generalized logistic.     

A Single Compartment Quantal Response Model with an Inspection Process

In a single compartment quantal response model, besides the input and release processes, an inspection process, assumed to be independent of the input and release processes, is considered. Each time when a release occurs, we assume the amount of release is randomly proportional to the amount present and the proportional rates form a sequence of independent and identically distributed random variables with support on [0, 1]. The input policy we consider is a modification of (s, S) input policy in the inventory model. More precisely, let 0 ≦s₂ ≦s₁ ≦s ≦ S, if after a release, the amount of the drug in subject's body is less than a level s₂ which is small enough, then there will be an input immediately with probability 1 — p and no more inputs thereafter with probability p, also there will be an input immediately if the dose level is in the interval [s₂, s₁). If the dose level is in the interval [s₁, s) there will be no input unless the inspector arrives. On the other hand, if the dose level is greater than or equal to s, then there will be no input. We consider a stochastic model as described above, and obtain the expressions for some quantities of interest. A Monte Carlo study has also been carried out to demonstrate some behaviors of our quantal response process.     

寄生蜂种群繁殖分布时间特征的研究

运用１０种寄生蜂的２３张生殖力表资料,分析比较了这些种群繁殖分布的特征．结果表明,寄生蜂种群繁殖具有相似的分布特征,种群繁殖集中分布在生殖头ｄ天内,在生殖头ｄ／２天内繁殖分布更为集中．在生殖头ｄ天内种群繁殖对种群增长的贡献几乎均达到１００％,其中大部分贡献是在生殖头ｄ／２天内实现的．这种繁殖分布特征对于寄生蜂种群内禀增长率的测定和掌握种群数量动态的时间特性十分重要．本文结合Ｉｗａｏ零频率法和Ｇｅｒｒａｒｄ阈限密度法,提出一种改进的种群密度估计方法──“综合阈限密度估计法”,并由此探讨了苹果树上山楂叶螨成螨的密度估计及其抽样技术．采用零样频率来估计成螨的平均密度,并得到用概率保证的理论抽样数模型．比较结果表明,零频率法所需的理论抽样数少于直接计数法．综合阈限密度估计法的拟合效果更为显著．     

山楂叶螨种群空间格局及其应用的研究Ⅱ．成螨种群密度综合估计及其抽样技术

本文结合Ｉｗａｏ零频率法和Ｇｅｒｒａｒｄ阈限密度法,提出一种改进的种群密度估计方法──“综合阈限密度估计法”,并由此探讨了苹果树上山楂叶螨成螨的密度估计及其抽样技术．采用零样频率来估计成螨的平均密度,并得到用概率保证的理论抽样数模型．比较结果表明,零频率法所需的理论抽样数少于直接计数法．综合阈限密度估计法的拟合效果更为显著．     

一类具有Crowley-Martin型的恒化器模型的定性分析

研究了恒化器中一类具有Crowley—Martin型功能反应函数的单种微生物培养系统,应用微分方程定性理论,得到微生物培养失败和成功的充分条件．最后给出本文的一个应用．     

具免疫时滞的HIV感染模型动力学性质分析

讨论了一类具免疫时滞的HIV感染模型.分析了未感染平衡点的全局渐近稳定性,给出了感染无免疫平衡点及感染免疫平衡点局部渐近稳定的充分条件.数值模拟结果表明,当易感细胞生成率的取值使得基本再生数满足平衡存在的条件且低于某一临界值时,时滞对平衡点的稳定性没有影响;若大于该临界值,随着时滞增大,稳定性开关发生,平衡点不稳定,出现一系列Hopf分支,最终表现为周期波动模式.     

多重二元响应Probit模型的渐近有效估计

针对多重二元响应Probit模型提出了两步估计方法,第一步由边际似然得到参数√n相合的估计,第二步通过一步迭代得到渐近有效估计,由于只需一步迭代,因此在利用模拟方法计算信息阵时,可以增加模拟的次数,从而减少模拟所产生的扰动对估计的影响．     

母源性抗-HBs对新生儿接种乙型肝炎疫苗的远期影响

目的:观察新生儿体内母源性乙型肝炎表面抗体(抗-HBs)对乙型肝炎疫苗接种后抗体应答的远期影响。方法:2006年10月-2007年1月在南京大学医学院附属鼓楼医院产前检查并住院分娩的单胎足月妊娠妇女中,选择抗-HBs阳性孕妇32例,抗-HBs阴性孕妇32例,其新生儿均按0、1、6方案接种重组(酵母)乙型肝炎疫苗,检测两组儿童乙型肝炎疫苗第3针接种后2年血清抗-HBs浓度。结果:新生儿接种乙型肝炎疫苗第3针后2年,母源性抗-HBs阴性组与阳性组儿童抗-HBs阳性率分别为90.6%与87.5%,其抗-HBs几何平均浓度分别为73.48mIU/ml与75.49mIU/ml,两组间抗-HBs阳性率与GMC的差异均无统计学意义(P=1.000,P=0.778);6例母源性抗-HBs>1000mIU/ml儿童中1例抗-HBs转阴(16.7%),而母源性抗-HBs<1000mIU/ml组和母源性抗-HBs组的儿童抗-HBs转阴率分别仅为7.69%和11.1%,但差异无统计学意(P=0.811)。结论:新生儿目前按照0,1,6方案接种乙型肝炎疫苗,能够有效保护其抵抗乙型肝炎病毒的感染;母源性抗-HBs对新生儿接种乙型肝炎疫苗...     

一类功能性反应模型在常数收获下的动态特性

具有功能性反应的捕食与被捕食模型具有非常复杂的动态性质．特别是在常数收获下,该模型呈现了各种各样、纷杂多变的动态特性。其中包括正平衡点及其稳定性的变化、各种分叉的产生以及周期解和极限环的出现．本文重点研究了常数收获项对一类功能性反应模型的动态性能的影响,得到了该收获模型存在稳定正平衡点、产生分叉以及在Hopf分叉附近产生周期解和极限环的若干充分条件．