Simple Formulae for Evaluating the Potential Impact of Confounding Bias

Unmeasured confounding is a common problem in observational studies. This article presents simple formulae that can set the bounds of the confounding risk ratio under three standard populations of the exposed, unexposed, and total groups. The bounds are derived by considering the confounding risk ratio as a function of the prevalence of a covariate, and can be constructed using only information about either the exposure–confounder or the disease–confounder relationship. The formulae can be extended to the confounding odds ratio in case–control studies, and the confounding risk difference is discussed. The application of these formulae is demonstrated using an example in which estimation may suffer from bias due to population stratification. The formulae can help to provide a realistic picture of the potential impact of bias due to confounding.     

Admissibility of a variance estimator in finite population sampling under Warner's randomized response plan with multiple responses

ABSTRACT

Let P be the proportion of individuals in a finite population possessing a sensitive attribute. We consider the problem of unbiased estimation of (i) the variance of a linear unbiased estimator of P and (ii) the population variance P (1—P) for a given probability sampling design under Warner's (1965 Warner, S.L. (1965). Randomized response - A survey technique for eliminating evasive answer bias. J. Amer. Statist. Assoc. 60:63–69.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) randomized response (RR) plan when independent responses are obtained from each sampled individual as many times as he/she is selected in the sample and prove the admissibility of a quadratic unbiased estimator for each.     

Reduced-Variance Methods for Detectability Correction of Population Abundance

Detectability issues create uncertainty in field surveys of animal and plant populations. Detectability correction is one method employed to deal with this problem when there is reasonable certainty that detectability is roughly constant with time or in different areas. Two new reduced-variance estimators of detectability are introduced and evaluated for the case of using a detectability correction for new areas that are surveyed only once. The new estimates are unbiased or nearly unbiased and produce population estimates with smaller variance than the Lincoln–Petersen estimate.     

Some improved ratio type estimators of population mean and ratio in finite population sample surveys

In this paper we present a class of ratio type estimators of the population mean and ratio in a finite population sample surveys with without replacement simple random sampling design, where information on an auxiliary variate x positively correlated with the main variate y is available. Large sample approximations to mean square errors (MSE) of these estimatorsare evaluated and their MSE's are compared with the MSE of the usual ratio estimator [ybar]_R of [ybar] the population mean of y. It is shown that under certain conditions these estimators are more efficient than [ybar]_R. When a prior knowledge of the value of thecoefficient of variation, c_y, of y is at hand, ratio type estimator, say [ybar]₁ of [ybar] is proposed. It is shown, under certain conditions, that [ybar]₁ is more efficient than [ybar]_R. When values of c_y, c_x and the population correlation coefficient ρ is at hand, then we have proposed another estimator, say [ybar]₂ of [ybar], which is always better than [ybar]_R as far as the efficiency is concerned. In fact, is [ybar] ₂ is shown to be even better than [ybar]₁. Finally estimators better than the usual ratio estimator [ybar]/[xbar] of [Ybar] are given.     

Non-parametric estimation of population size from capture–recapture data when the capture probability depends on a covariate

Summary.  In capture–recapture experiments the capture probabilities may depend on individual covariates such as an individual's weight or age. Typically this dependence is modelled through simple parametric functions of the covariates. Here we first demonstrate that misspecification of the model can produce biased estimates and subsequently develop a non-parametric procedure to estimate the functional relationship between the probability of capture and a single covariate. This estimator is then incorporated in a Horvitz–Thompson estimator to estimate the size of the population. The resulting estimators are evaluated in a simulation study and applied to a data set on captures of the Mountain Pygmy Possum.     

关于中国人口控制问题的商榷

中国人口占世界人口1/5,是世界人口最多的发展中国家。中国政府把计划生育政策定为基本国策,并取得了举世瞩目的成就。中国人口基数过大,人均耕地远小于国土面积与中国相当的美国,加上其他不利因素,经有关专家组研究,中国最大环境人口容量为16亿。又经预测,按现行中国人口政策,到2030年前后中国人口将达到16亿。中国人口控制喜忧参半,仍十分严峻,且任重而道远。因此,讨论了中国人口控制的成就和问题,并提出了若干建议供参考。     

中国少数民族村寨人口流动特征及其影响因素分析

根据28个不同的少数民族村寨的人口流动数据资料,将其分为推力拉力不足类型、推力拉力共同作用类型、文化风俗影响类型、开发程度制约类型、开放程度推动类型、跨境收入拉动类型6种,对其人口流动的特征、规律和影响因素进行了归纳。     

论中国的人口控制与可持续发展

当代全球性的资源短缺、环境恶化、失业危机和贫困蔓延,使人类社会面临着不可持续发展的严重威胁,导致这种状况的根源则是人口规模的持续膨胀,因此“人类对生育的选择将决定世界的未来”已成为全球的共识,我国虽已成功地实现了人口低速增长的历史性转变,但未达人口最高峰前的惯性膨胀、就业和消费压力及老龄化困惑,不仅加剧着资源紧缺和环境恶化,也给社会稳定和人们生活质量的提高造成了沉重的背负。因而,只有持续地控制人口增长、提高人口素质和合理人口分布,才能最终实现我国的可持续发展。     

生育政策调整及其风险规避

现行生育政策对遏制中国人口过快增长作出了历史性贡献,但是政策本身具有阶段性和局限性,不宜长期实行,否则会因下一代人口的过快衰减而影响家庭、社会甚至国防安全。为了让公民满足在生育上的刚性需求和实现平等的生育权利以及降低政策的负面影响,建议将现行生育政策调整为全国统一的“补偿一孩,允许二孩,控制三孩”,并将这一政策延续到2033年前后。调整生育政策可能会出现生育率波动、推迟和抬高人口峰值、计划生育工作滑坡、独生子女家庭总负担加重、人口与资源生态环境关系更加紧张等风险,需要切实规避。     

西北农村人口对生态环境的压力与生态移民的战略选择

人口与生态环境问题密切相关,对大量数据、指标的分析结果表明,西北农村地区人口对生态环境造成的压力已经十分严重,生态移民是最重要的缓解人口压力的途径。目前生态移民实践相对于生态环境保护的要求还存在一定差距,因此,还必须进一步加大生态移民的力度,拓宽生态移民的安置途径,把生态移民与农村城镇化发展结合起来,才能最终从根本上解决生态移民问题。