统计数据准确性评估的误差效应分析方法

基于统计数据生产者角度开发有效而可靠的统计数据准确性评估方法,具有迫切的必要性.参照社会调查领域的计量误差效应评估技术,结合中国政府统计调查数据的结构特征,可以构造针对宏观统计数据的误差效应模型,从个体数据与总量数据两个层次、针对系统偏差与方差两类误差效应来定义统计数据的准确性.通过对该模型中若干重要参数的识别估计,既能实现传统的统计偏差评估,又可揭示因操作因素、制度因素、基层单元属性特征等对于统计数据准确性所造成的影响,从中发现重要的统计误差来源,从而推动统计方法制度进行有针对性地改革与完善.     

基于SAM的宏观统计数据质量评估方法研究

数据质量评估是统计数据质量管理的重要环节。从SAM核算框架入手,提出了宏观统计数据质量的评估方法,主要包括等量核算指标体系评估方法、账户平衡指标体系评估方法及"问题型"评估方法,以期从SAM的角度为宏观统计数据质量的甄别和提高提供一种研究方法。     

统计数据质量评价方法与误差分布研究

我国统计数据质量的评价方法主要有逻辑性评价方法、从异常值角度评估、从误差角度评估、Bayes决策法以及SARIMA等。文章认为,我国统计数据质量不高的主要原因在于统计数据失真,不完整,时效性差,适用性不强,非同一性,统计手段和方法落后以及逻辑分析不合理等。其误差分布的来源在于系统性误差,这些误差存在于调查的设计、实施、计量和整合等阶段。     

GDP数据质量评估方法研究

GDP数据质量备受关注。本文介绍了逻辑关系检验法等几种统计数据质量评估办法,指出目前国家统计局针对地区GDP数据质量的评估办法中存在的问题,并提出了改进思路。     

我国统计数据质量的评估方法研究————————趋势模拟评估法及其应用

 本文采用组合模型的形式对时间序列数据的变化特点建模，在模型通过各种检验、具有良好统计预测功能的基础上，从检验异常值的角度来分析预测值与实际值之间差异的程度，找出离群数据，利用数理统计中检验实验观测数据异常值的方法，对离群数据的误差进行统计上的显著检验，从而评估统计数据的质量。文章以我国国内生产总值（GDP）为研究对象，选取我国1978-2003年间的GDP作为样本，运用趋势模拟评估法来评估我国2004年国内生产总值的准确性。对我国经济指标的时间序列数据进行了实证分析。     

中国GDP核算误差的特征事实与发生机制——兼论计量模型方法对于GDP数据质量的评估功效

基于GDP数据的历史修订与地区差异情况,依照反事实分析的推理逻辑,考察GDP核算误差的特征事实,探讨其中覆盖误差、操作误差以及估算误差的发生机制与影响模式。结果表明,在各年份现价GDP数据中,由覆盖误差和估算误差造成的综合效应是以系统性的低估为主,其中服务业部门是核算误差的主要来源所在;地区层级GDP核算过程中覆盖误差、估算误差与操作误差的综合效果以持续性的数据高估为主,其中的操作误差效应也会存在于国家层级的GDP核算中。由于缺乏对于GDP核算误差发生机制的必要考虑,计量模型方法在评估GDP数据质量中的功效非常有限。     

统计数据质量监控和评估方法研究(下)

从探索建立上海市统计系统数据质量监控和评估体系方法角度出发,结合统计"四大工程"建设和一套表工作的实施,对统计数据质量监控的管理从统计设计、统计培训等五个阶段提出了工作要求和方法。目前统计数据质量评估的方法有历史数据对比分析、趋势性对比分析等。为进一步完善统计数据质量监控和评估体系,建议提高统计数据质量的监控和评估效果、建立健全下级统计机构的数据质量考核机制等。     

数据质量控制与评估办法

数据质量控制与评估办法数据质量是统计工作的生命，数据质量控制与评估应该说贯穿于整个统计工作过程。一、统计数据质量控制与评估的必要性和迫切性二、统计数据质量控制与评估的几种方法（一）比较分析法（二）调查验证法（三）专家论证法三、市县级统计部门关于数据质...     

基于云理论的统计信息质量评估方法研究

针对统计信息质量评估方法的问题,给出一种基于云理论的统计数据质量评估方法。首先,确定云模型的评价等级语言粒度,对其进行软划分,并根据统计数据质量的评价指标体系从八个维度刻划数据质量评估云模型,利用云模型加权算术平均集成技术构造评价综合云;其次,结合云模型相似性的测度方法,根据综合云与评价等级云模型的相似度判断统计数据质量评估综合云的隶属等级。最后,通过实例表明方法的可行性和有效性,新方法可以作为统计数据质量评估和监管的一个参考。     

基于经典计量模型的统计数据质量评估方法

 本文以经济理论为基础,从整个经济系统出发,利用研究对象的相关影响因素构造计量模型,在既定模型下,运用异常值的检验方法及统计诊断原理进行数据质量的定量评估。通过选择合适的模型对考察对象的变化规律进行模拟,找出异常数据（离群值）,判断异常数据是否显著异常,对异常数据进行多方查证和原因分析来进一步判断数据的质量,并对我国的统计数据质量进行了实证分析。     

宏观统计数据质量评估的研究范畴与基本范式

 内容提要：不断推进宏观统计数据质量评估研究的体系化和规范化,是该领域学术价值存续和有效信息揭示的必由出路。本文旨在解决其中的两方面关键问题：一是界定宏观统计数据质量评估的研究范畴,藉此明晰数据质量评估研究的概念结构、方法原理、理论基础和功能边界;二是探讨对各种宏观统计数据质量评估方法的适用性进行检验的可行方法,以确保评估研究可以给出较为可靠的结论。进而明确宏观统计数据质量评估研究的基本范式,探讨研究中应遵循的一系列操作规则。     

Assessing student learning in the context of evaluating a chance course

This paper describes the use of different assessment methods to evaluate Chance courses in the NSF-funded Chance project. Multiple methods were used to measure changes in students' attitudes and beliefs about statistics, reasoning about probability and statistics, and ability to critique a newspaper article that reports statistical results. Samples of assessment materials and scoring rubrics used in the evaluation are included.     

On estimands and the analysis of adverse events in the presence of varying follow‐up times within the benefit assessment of therapies

The analysis of adverse events (AEs) is a key component in the assessment of a drug's safety profile. Inappropriate analysis methods may result in misleading conclusions about a therapy's safety and consequently its benefit‐risk ratio. The statistical analysis of AEs is complicated by the fact that the follow‐up times can vary between the patients included in a clinical trial. This paper takes as its focus the analysis of AE data in the presence of varying follow‐up times within the benefit assessment of therapeutic interventions. Instead of approaching this issue directly and solely from an analysis point of view, we first discuss what should be estimated in the context of safety data, leading to the concept of estimands. Although the current discussion on estimands is mainly related to efficacy evaluation, the concept is applicable to safety endpoints as well. Within the framework of estimands, we present statistical methods for analysing AEs with the focus being on the time to the occurrence of the first AE of a specific type. We give recommendations which estimators should be used for the estimands described. Furthermore, we state practical implications of the analysis of AEs in clinical trials and give an overview of examples across different indications. We also provide a review of current practices of health technology assessment (HTA) agencies with respect to the evaluation of safety data. Finally, we describe problems with meta‐analyses of AE data and sketch possible solutions.     

中国统计数据质量理论研究与实践历程

本文通过对改革开放以来我国统计数据质量理论研究和实践成果的回顾,归纳出三十年来有关统计数据质量的理论研究和实践脉络。在总结三十年来我国统计数据质量说取得的理论与实践成就的基础上,分析了存在的问题及面临的挑战。     

Comparing a survey and a conjoint study: the future vision of water intermediaries

This paper compares and contrasts two methods of obtaining opinions using questionnaires. As the name suggests, a conjoint study makes it possible to consider several attributes jointly. Conjoint analysis is a statistical method to analyse preferences. However, conjoint analysis requires a certain amount of effort by the respondent. The alternative is ordinary survey questions, answered one at a time. Survey questions are easier to grasp mentally, but they do not challenge the respondent to prioritize. This investigation has utilized both methods, survey and conjoint, making it possible to compare them on real data. Attribute importance, attribute correlations, case clustering and attribute grouping are evaluated by both methods. Correspondence between how the two methods measure the attribute in question is also given. Overall, both methods yield the same picture concerning the relative importance of the attributes. Taken one attribute at a time, the correspondence between the methods varies from good to no correspondence. Considering all attributes together by cluster analysis of the cases, the conjoint and survey data yield different cluster structures. The attributes are grouped by factor analysis, and there is reasonable correspondence. The data originate from the EU project 'New Intermediary services and the transformation of urban water supply and wastewater disposal systems in Europe'.     

Adjusting overall survival for treatment switches: commonly used methods and practical application

In parallel group trials, long‐term efficacy endpoints may be affected if some patients switch or cross over to the alternative treatment arm prior to the event. In oncology trials, switch to the experimental treatment can occur in the control arm following disease progression and potentially impact overall survival. It may be a clinically relevant question to estimate the efficacy that would have been observed if no patients had switched, for example, to estimate ‘real‐life’ clinical effectiveness for a health technology assessment. Several commonly used statistical methods are available that try to adjust time‐to‐event data to account for treatment switching, ranging from naive exclusion and censoring approaches to more complex inverse probability of censoring weighting and rank‐preserving structural failure time models. These are described, along with their key assumptions, strengths, and limitations. Best practice guidance is provided for both trial design and analysis when switching is anticipated. Available statistical software is summarized, and examples are provided of the application of these methods in health technology assessments of oncology trials. Key considerations include having a clearly articulated rationale and research question and a well‐designed trial with sufficient good quality data collection to enable robust statistical analysis. No analysis method is universally suitable in all situations, and each makes strong untestable assumptions. There is a need for further research into new or improved techniques. This information should aid statisticians and their colleagues to improve the design and analysis of clinical trials where treatment switch is anticipated. Copyright © 2013 John Wiley & Sons, Ltd.     

统计数据质量与用户满意度：测评量表设计与实证研究

 针对政府统计数据质量评估问题,综合若干国家统计部门与国际组织对统计质量的定义,确立政府统计数据质量维度体系;进而参照国际货币基金组织的“数据质量评估框架”设计具体的用户满意度测评量表。基于该量表的问卷调查结果显示,量表具有良好的测量信度与效度。研究中提出的八项质量维度可以充分反映政府统计数据质量的不同侧面,可以有效解构用户满意度的特征;用户对各质量维度的重要性认知、用户专业技术职务、对统计数据的依赖程度以及搜集渠道的选择等,与其满意度之间亦表现出明显的关联模式。     

周期性普查数据质量评估方法与适用性研究

从普查数据准确性检验到普查数据误差测量,有关周期性普查数据质量的评估研究随着人们对普查数据生产过程的认识而不断发展与完善,先后发展出包括人口统计分析、数据一致性检验、行政记录审核和事后质量抽查等技术思路,包含多种具体的评估方法。根据评估依据与普查系统的关系,这些评估方法可被归纳为内部评估、外部评估以及事后抽查等三种评估途径。通过对每种评估方法特点及其适用性的分析,有利于进一步深化我国周期性普查数据质量评估的理论研究。