企业市场调查中随机化回答技术的应用

随机化回答技术十分适宜调查敏感性问题并获得相关资料.在企业市场调查中应用随机化回答技术有利于获得敏感性资料,减少调查误差,提高企业竞争力和企业科学管理水平.文章以非工资性收入调查为例,说明了如何组合应用西蒙斯模型法与格林伯格非相关模型法.     

基于随机化回答模型的最低工资敏感性问题研究

针对最低工资调查中出现的敏感性问题,引入随机化回答技术,并针对定性和定量两类敏感性问题,分别引入不同的随机化回答模型。同时还考虑到最低工资调查中,不同调查单位对同一问题敏感程度不相同的特性,在定量问题的随机化回答模型中引入敏感性水平,对原有模型进行有效的改进,使被调查者能够更加积极配合最低工资调查,从而能够进一步减少由于各类敏感性问题造成的非抽样误差。这套随机化处理方法还可推广应用到其他类型的敏感性问题中。     

敏感性问题调查的新方法——网上调查

一、网上敏感性问题调查的含义抽样调查技术中有一项独特的调查技术,即敏感性问题的随机化回答技术.所谓敏感性问题,就是所调查内容涉及私人机密而不愿或不便于公开表态或陈述的问题. 这类问题涉及到被调查者的隐私,如赌博、吸毒、婚前性行为、偷税漏税等.如果直接提问,易引起反感,或者得不到真实回答,或者遭到拒绝,无法得到结果.尽管国外已设计出随机化回答技术对此类问题进行调查,但调查方式陈旧、不     

对敏感性问题调查之随机化回答技术的思考

引起抽样的数据产生无回答现象的原因很多，就被调查对象而言，经常会发生因调查内容涉及敏感性问题而导致被调查对象有意识不回答的现象。何谓敏感性问题？敏感性问题是指所调查的内容涉及私人机密而不愿或不便于公开表态或陈述的问题。例如在考试中的学生作弊现象，工商业者的偷税漏税问题，司机的违例驾驶等问题就是一般人不愿正面回答的敏感性问题。可以预见，在调查这一类问题时阻力很大，结果要么是引起被调查者能对所调查者的反感──他们直接拒绝回答，要么是被调查者给出并不真实的回答。有鉴于此，需要有一种经过特别设计的回答技…     

企业市场调查中敏感性问题的处理

信息时代的发展要求企业掌握及时、准确。可靠的数据资料以把握市场机遇,其中企业进行与自身产品、服务相关的市场调查不失为一种有效获取市场信息的方法。企业市场调查是一门新兴的管理技术,是减少决策主观性、增强产品竞争力。提高企业经济效益的有效工具。但就我国目前的市场调查而言,它尚处于起步阶段,属一个全新的行业,而且主要为调查公司实施的社会状况及热点问题调查,由企业为掌握市场信息、避免决策失误自行实施的市场调查少之甚少。这样无论从调查方法、调查模式,还是从调查人员素质来说,我国的企业市场调查有众多未解决的问题。就敏感性问题而言,它虽是市场调查中调查人员所竭力避免的,但有时无法回避。非问不可。这样无论是企业市场调查,还是敏感性问题调查,都是我国目前的薄弱环节,都迫切需要更为有效的技术支持。为了更好地处理企业市场调查中所遇到的敏感性问题,我们在分析随机化回答模型的基础上,提出一种新的解决思路,供企业市场调查者参考。     

随机化回答技术调查“敏感性问题”的博弈分析及设计改进——对一次沃纳方法调查实践的分析思考

沃纳方法等随机化回答技术是对“敏感性问题”调查的创新之举，但调查实践显示调查对象是否如实回答值得研究，博弈分析表明，随机化回答技术的有效性与调查对象对“群体性特征”的曝露是否敏感有关，据此，应改进调查设计和组织。     

随机化回答技术在敏感性问题调查中的一种新应用

最近,在我们开展的一次关于深圳市居民生活水平调查时遇到这样一个问题:我们需要知道深圳居民的银行存款状况,所以拟了以下一个调查问题:“您现在的银行存款是()?以下有六个备选项,⑴3万以下;⑵3-10万;⑶10-30万;⑷30-50万;⑸50-80万;⑹80万以上。”很显然该问题属于强敏感性问题,因此被调查者极有可能出于保护个人隐私而拒绝回答或作虚假回答。解决敏感性调查问题比较科学和常用的方法就是随机化回答技术。随机化回答技术最早由沃纳(Warner)于1965提出,之后就有很多人提出改进的随机化回答模型,如双无关问题模型、隐含的随机化回答模型、随机截尾的Warner与Sim-mons模型等。从二项选择到多项选择、从定性到定量,随机化回答技术在解决敏感性问题调查方面日渐完善。理论的可行性和操作的简便性是设计随机化回答模型的基本要求也是设计的难点。目前,很多的模型在理论的可行性方面无可非议,但其过于繁琐的操作规则使模型的价值大打折扣。本文旨在通过对西蒙斯随机化回答模型作一定延伸,从而获得解决多项选择的敏感性调查问题的一种易于操作的方法。     

敏感性问题调查法效率的比较

一、引言 "随机化回答"调查技术是人类针对社会和经济现象中敏感性问题调查时的一项极富智慧的技术创造.     

沃纳模型的缺陷及其改进

一、沃纳模型的基本思想 沃纳模型是沃纳(Warner)于1965年首先提出的一种随机化回答模型.该模型是为了解决社会经济现象中敏感性问题而采用的一种随机化回答技术.模型设计的基本思想是:为了调查某个敏感性问题,同时列出两个存在相关关系的问题制成卡片(一个问题是具有某种特征为卡片A,另一个问题是不具有某种特征为卡片B),被调查者随机抽取卡片(不告诉调查人员)进行回答,回答后,卡片不退还调查人员.这种设计,使调查人员不知道被调查者在回答哪一个问题,在一定程度上消除了被调查者的担心和顾虑,使他们参与调查,从而实现了被调查者提供真实情况的自我保护.同时,调查人员还可以通过对所有调查结果的汇总,利用概率原理推算得到总体中具有该特征人数比例的估计值.其模型公式为:     

敏感性问题调查的基本方法与比较

抽样调查中 ,经常会遇到敏感性问题的调查工作 ,由于涉及到被调查者的隐私问题 ,很难得到被调查者的配合 ,因此造成了调查的困难、调查结果的不准确。文章系统介绍了处理敏感性问题调查的基本方法 ,即沃纳模型和西蒙斯模型。在此基础上阐述其改进方法——随机变量和回答模型 ,并对各种方法进行了比较     

Sample size allocation in multiregional equivalence studies

With the increasing globalization of drug development, the multiregional clinical trial (MRCT) has gained extensive use. The data from MRCTs could be accepted by regulatory authorities across regions and countries as the primary sources of evidence to support global marketing drug approval simultaneously. The MRCT can speed up patient enrollment and drug approval, and it makes the effective therapies available to patients all over the world simultaneously. However, there are many challenges both operationally and scientifically in conducting a drug development globally. One of many important questions to answer for the design of a multiregional study is how to partition sample size into each individual region. In this paper, two systematic approaches are proposed for the sample size allocation in a multiregional equivalence trial. A numerical evaluation and a biosimilar trial are used to illustrate the characteristics of the proposed approaches.     

The Analysis of Survey Data with Framing Effects

A well-known difficulty in survey research is that respondents’ answers to questions can depend on arbitrary features of a survey’s design, such as the wording of questions or the ordering of answer choices. In this paper, we describe a novel set of tools for analyzing survey data characterized by such framing effects. We show that the conventional approach to analyzing data with framing effects—randomizing survey-takers across frames and pooling the responses—generally does not identify a useful parameter. In its place, we propose an alternative approach and provide conditions under which it identifies the responses that are unaffected by framing. We also present several results for shedding light on the population distribution of the individual characteristic the survey is designed to measure.     

How to ask sensitive multiple-choice questions

Motivated by recent failures of polling to estimate populist party support, we propose and analyze two methods for asking sensitive multiple-choice questions where the respondent retains some privacy and therefore might answer more truthfully. The first method consists of asking for the true choice along with a choice picked at random. The other method presents a list of choices and asks whether the preferred one is on the list or not. Different respondents are shown different lists. The methods are easy to explain, which makes it likely that the respondent understands how her privacy is protected and may thus entice her to participate in the survey and answer truthfully. The methods are also easy to implement and scale up.     

Structurally consistent probabilities of selecting answers

This paper offers a procedure for specifying probabilities for students to select answers on a multiple-choice test that, unlike previous procedures, satisfies all three of the following structural consistency conditions: (1) for any student, the sum over questions of the probabilities that the student will use the correct answers is the student's score on the test; (2) for any student, the sum over possible answers of the probabilities of using the answers is 1.0; and (3) for any answer to any question, the sum over students of the probabilities of using that answer is the number of students who used that answer. When applied to an exam, these fully consistent probabilities had the same power to identify cheaters as the probabilities proposed by Wesolowsky, and noticeably better power than the probabilities suggested by Frary et al.     

Tagging and deportation: who gets it right?

The Home Office in England suffered major embarrassment this year over its failure to deport foreign nationals who had served prison sentences. It could not even supply statistics on how many there were, or what crimes they may have committed after release. Scotland, in contrast, could answer such questions with ease. Sheila Bird investigates English failure and Scottish solutions.     

Randomized response technique in a National Survey

In order to produce estimates of the number of women having abortions during a 12-month period in the conterminous United States, the randomized response technique was used in the 1973 National Survey of Family Growth. The model applied used 2 unrelated questions in separate half-samples, with a coin as the randomizing device. The randomized response technique resulted in a higher estimate for the number of women with abortions that has previously been obtained through direct questions or reporting systems. The overall estimated proportion who had abortions among women who had been married or who had their own children in the household is 3.0% with a standardized error of 0.8 percentage points; however, there is a wide variation in the half-sample estimates of abortion. Differences between the 2 half-samples led to an examination of possible measurement error. 3 types of errors in measurement which may affect the estimate based on the randomized response technique are: 1) error in the answer to the sensitive question on abortion under the randomized response conditions; 2) error in the answer to the innocuous question under randomized response conditions; and 3) error in the answer to the innocuous question when asked directly. Comparisons between data from the different sources for currently married women suggest that all differences are not due to measurement error and that a large number of women had an unreported and/or illegal abortion in 1973. Although the randomized response models have been in use for at least 10 years, there continues to be a need for work on the field administration and subsequent analysis of these models.     

Regression Using Pairs vs. Regression on Differences: A Real-life Case Study for a Master's Level Methods Class

When teaching regression classes real-life examples help emphasize the importance of understanding theoretical concepts related to methodologies. This can be appreciated after a little reflection on the difficulty of constructing novel questions in regression that test on concepts rather than mere calculations. Interdisciplinary collaborations can be fertile contexts for questions of this type. In this article, we offer a case study that students will find: (1) practical with respect to the question being addressed, (2) compelling in the way it shows how a solid understanding of theory helps answer the question, and (3) enlightening in the way it shows how statisticians contribute to problem solving in interdisciplinary environments. Supplementary materials for this article are available online.     

Scrambled randomized response methods for obtaining sensitive quantitative data

We study a multiplicative randomized response method for obtaining responses to sensitive questions when the answers are quantitative. The method involves the respondent multiplying his sensitive answer by a random number from a known distribution, and giving the product to the interviewer, who does not know the value of the random number and thus receives a scrambled response. Some particular distributions for the random scrambling number are proposed and studied, and ways of generating the scrambling numbers are discussed. Some modifications for increasing the efficiency of the method are proposed, and numerical results are given that show the scrambled response method is generally superior to the previously used method of randomizing questions.     

A temporal correlation function for the association between patient‐reported outcome and clinical endpoints

For clinical trials with multiple endpoints, the primary interest is usually to evaluate the relationship of these endpoints and treatment interventions. Studying the correlation of two clinical trial endpoints can also be of interests. For example, the association between patient‐reported outcome and clinically assessed endpoint could answer important research questions and also generate interesting hypothesis for future research. However, it is not straightforward to quantify such association. In this article, we proposed a multiple event approach to profile such association with a temporal correlation function, visualized by a correlation function plot over time with a confidence band. We developed this approach by extending the existing methodology in recurrent event literature. This approach was shown to be generally unbiased and could be a useful tool for data visualization and inference. We demonstrated the use of this method with data from a real clinical trial. Although this approach was developed to evaluate the association between patient‐reported outcome and adverse events, it can also be used to evaluate the association of any two endpoints that can be translated to time‐to‐event endpoints. Copyright © 2015 John Wiley & Sons, Ltd.     

官方统计应如何面对Big Data 的挑战

 随着信息化、网络化时代的到来,"Big Data"的浪潮为整个社会带来了信息金矿,也给官方统计带来了挑战。本文对官方统计应该如何正确认识"Big Data”,如何积极应对“Big Data”带来的挑战,进行了初步分析,给出了作者的明确回答。