Remote access systems for statistical analysis of microdata

Statistical Agencies manage huge amounts of microdata. The main task of these agencies is to provide a variety of users with general information about for instance the population and the economy. However, in some cases users request additional, more specific information. Many agencies have therefore set up facilities that enable selected users to obtain tailor-made statistical information.A remote access system is an example of such a facility where users can submit queries for statistical information from their own computer. These queries are handled by the statistical agency and the generated, possibly confidentialised, output is returned to the user. This way the agency still keeps control over its own data while the user does not need to make frequent visits to the agency.For some years, the Luxembourg Income Study (LIS) and Luxembourg Employment Study (LES) have made use of an advanced remote access system. At Statistics Netherlands and at other statistical institutes recently the need for a similar system has been expressed. In this article, we discuss the characteristics, limitations and desired properties of a remote access system. We illustrate the discussion by the system used at LIS/LES.     

Statistical quality control at statistics canada

Over the past several years statistical quality control methodologies at Statistics Canada have evolved frotn forrnal Product Control (k Acceptance Sampling By Attributes) to a more complete use of all quality control information obtained to achieve what is now called Acceptance Control. The use of this additional information allows us to continually adapt our quality control methods to the existing conditions of survey operations. In this context this paper reviews the general approach to statistical quality control and its relation to survey processing operations in Statistics Canada.     

Quality control procedures at statistics sweden

This paper treats quality control in a wide sense which is imperative for a statistical agencyto do. First, we discuss the meaning of total survey error and different quality characteris-

tics. Secondly, some common quality problems in statistical agencies are presented as a prelude to the bulk of this paper, namely the case of Sweden. Quality control efforts at Statistics Sweden are reviewed regarding the handling of specific error sources, error estimation, and error control. Different tools such as preventive control, production control, and evaluation are dealt with. As for QC-procedures proper we provide some applications from clerical coding.     

Testing homogeneity in a multivariate mixture model

Testing homogeneity is a fundamental problem in finite mixture models. It has been investigated by many researchers and most of the existing works have focused on the univariate case. In this article, the authors extend the use of the EM‐test for testing homogeneity to multivariate mixture models. They show that the EM‐test statistic asymptotically has the same distribution as a certain transformation of a single multivariate normal vector. On the basis of this result, they suggest a resampling procedure to approximate the P‐value of the EM‐test. Simulation studies show that the EM‐test has accurate type I errors and adequate power, and is more powerful and computationally efficient than the bootstrap likelihood ratio test. Two real data sets are analysed to illustrate the application of our theoretical results. The Canadian Journal of Statistics 39: 218–238; 2011 © 2011 Statistical Society of Canada     

No islands: charting a course for UK official statistics

Our system of official statistics in the UK is one of the most decentralised and elaborate in the world. As well as the Office for National Statistics (ONS), it spans several sizeable centres of expertise in Whitehall departments and in the three devolved administrations; and it embraces agencies such as the Higher Education Statistics Agency and the Information Centre for Health and Social Care, which sit at arms length from central departments. In 2008, legislation establishing a new Statistics Board, with oversight not just of the ONS but of all official figures produced by these bodies, will come fully into force. Richard Alldritt of the Statistics Commission and Richard Laux of the ONS identify some of the challenges facing the statistical system at this time of transition and suggests a course that the Statistics Board might want to steer.     

二级统计体系在中国的可行性探讨

文章指出:中国政府统计体系的根本问题在于机构层层设置所导致的效率低下,而克服当前困境的根本出路在于减少机构层次。从长远看,由国家统计局和县级统计局构成的二级统计体系是中国政府统计体系改革的目标模式。     

加拿大资源环境统计与核算的主要内容和方法

 加拿大统计局资源环境核算工作在国际统计领域处于领先水平，并为其他国家开展此项工作提供了许多有益的方法和经验。本文主要对加拿大的资源环境核算总体框架、自然资源存量账户、物质和能源流量账户、环境保护支出账户及工作情况等内容进行了较为全面系统的介绍和论述。     

Estimation of a semiparametric recursive bivariate probit model in the presence of endogeneity

The classic recursive bivariate probit model is of particular interest to researchers since it allows for the estimation of the treatment effect that a binary endogenous variable has on a binary outcome in the presence of unobservables. In this article, the authors consider the semiparametric version of this model and introduce a model fitting procedure which permits to estimate reliably the parameters of a system of two binary outcomes with a binary endogenous regressor and smooth functions of continuous covariates. They illustrate the empirical validity of the proposal through an extensive simulation study. The approach is applied to data from a survey, conducted in Botswana, on the impact of education on women's fertility. Some studies suggest that the estimated effect could have been biased by the possible endogeneity arising because unobservable confounders (e.g., ability and motivation) are associated with both fertility and education. The Canadian Journal of Statistics 39: 259–279; 2011 © 2011 Statistical Society of Canada     

国际上对国家统计机构的综合比较及其评价

自20世纪80年代以来,随着信息技术的迅猛发展,一些国家的统计机构面临着国内外变化的巨大压力。一方面,认为计算机网络技术的应用普及,国家统计机构应相应减少经费开支和统计人员数量,减轻社会统计调查负担。例如,北欧一些国家政府提出削减统计预算支出政策,国家统计机构面临着提高统计工作运行效率的内部压力。另一方面,全球经济一体化进程的加快,使得视作国家统计机构生命的统计数据质量日益受到国内外政府和有关组织的高度重视,特别是在墨西哥、亚洲金融危机之后。国际社会普遍认为,统计数据失真、数据不完整、公布不及时、对社会需求反…     

Testing for order among K populations: theory and examples

Testing for stochastic order among K populations is a common and important problem in statistical practice. It arises in the analysis of both planned experiments and observational studies. The authors develop a new nonparametric test for order among K populations that can accommodate any stochastic ordering. The test is based on a maximally selected chi‐bar‐square statistic. The authors find its limiting distribution and use simulations to derive critical values. Three important examples are used to illustrate the applicability of the general method. The authors find that the new tests outperform the existing methods in many practical cases. The Canadian Journal of Statistics 38: 97–115; 2010 © 2009 Statistical Society of Canada     

Duration analysis in longitudinal studies with intermittent observation times and losses to followup

We consider the analysis of spell durations observed in event history studies where members of the study panel are seen intermittently. Challenges for analysis arise because losses to followup are frequently related to previous event history, and spells typically overlap more than one observation period. We provide methods of estimation based on inverse probability of censoring weighting for parametric and semiparametric Cox regression models. Selection of panel members through a complex survey design is also addressed, and the methods are illustrated in an analysis of jobless spell durations based on data from the Statistics Canada Survey of Labour and Income Dynamics. The Canadian Journal of Statistics 40: 1–21; 2012 © 2012 Statistical Society of Canada     

Perturbed robust linear estimating equations for confidentiality protection in remote analysis

National statistical agencies and other data custodians collect and hold a vast amount of survey and census data, containing information vital for research and policy analysis. However, the problem of allowing analysis of these data, while protecting respondent confidentiality, has proved challenging to address. In this paper we will focus on the remote analysis approach, under which a confidential dataset is held in a secure environment under the direct control of the data custodian agency. A computer system within the secure environment accepts a query from an analyst, runs it on the data, then returns the results to the analyst. In particular, the analyst does not have direct access to the data at all, and cannot view any microdata records. We further focus on the fitting of linear regression models to confidential data in the presence of outliers and influential points, such as are often present in business data. We propose a new method for protecting confidentiality in linear regression via a remote analysis system, that provides additional confidentiality protection for outliers and influential points in the data. The method we describe in this paper was designed for the prototype DataAnalyser system developed by the Australian Bureau of Statistics, however the method would be suitable for similar remote analysis systems.     

Validity and efficiency in analyzing ordinal responses with missing observations

This article addresses issues in creating public-use data files in the presence of missing ordinal responses and subsequent statistical analyses of the dataset by users. The authors propose a fully efficient fractional imputation (FI) procedure for ordinal responses with missing observations. The proposed imputation strategy retrieves the missing values through the full conditional distribution of the response given the covariates and results in a single imputed data file that can be analyzed by different data users with different scientific objectives. Two most critical aspects of statistical analyses based on the imputed data set,  validity  and  efficiency, are examined through regression analysis involving the ordinal response and a selected set of covariates. It is shown through both theoretical development and simulation studies that, when the ordinal responses are missing at random, the proposed FI procedure leads to valid and highly efficient inferences as compared to existing methods. Variance estimation using the fractionally imputed data set is also discussed. The Canadian Journal of Statistics 48: 138–151; 2020 © 2019 Statistical Society of Canada     

统计虚假成因及治理对策研究

《统计法》已实施20余年,但统计数据虚假现象仍然十分严重。文章从统计体制、统计方法、执法缺陷等方面探析了统计数据虚假成因及治理对策。同时,现行《统计法》亟需修改完善。     

Was the conservative majority predictable?

Canada's $41{\rm st}$ national general election saw the Conservative Party increase its seat count from 143 to 166, thus giving it a majority of the national parliament's 308 seats. By contrast, nearly all of the pre‐election seat count forecasts predicted a Conservative minority only. We examine the extent to which simple statistical models could or could not have predicted the Conservative majority prior to the election. We conclude that, by using data from the previous (2008) election appropriately, the Conservative majority should have been anticipated as the most likely outcome. The Canadian Journal of Statistics 39: 721–733; 2011. © 2011 Statistical Society of Canada     

All Data are Wrong,but Some are Useful? Advocating the Need for Data Auditing

In a recent article from the Annals of Applied Statistics, Cox discussed the main phases of applied statistical research ranging from clarifying study objectives to final data analysis and interpreting results. As an incidental remark to these main phases, we advocate that beyond cleaning and preprocessing the data, it is a good practice to audit the data to determine if they can be trusted at all. A case study based on Ghanaian Official Fishery Statistics is used to illustrate this need, with Benford's law being the tool used to carrying out the data audit. Supplementary materials for this article are available online.     

Asymptotic properties of maximum weighted likelihood estimators

The relevance weighted likelihood method was introduced by Hu and Zidek (Technical Report No. 161, Department of Statistics, The University of British Columbia, Vancouver, BC, Canada, 1995) to formally embrace a variety of statistical procedures for trading bias for precision. Their approach combines all relevant information through a weighted version of the likelihood function. The present paper is concerned with the asymptotic properties of a class of maximum weighted likelihood estimators that contains those considered by Hu and Zidek (Technical Report No. 161, Department of Statistics, The University of British Columbia, Vancouver, BC, Canada, 1995, in: Ahmed, S.E. Reid, N. (Eds.), Empirical Bayes and Likelihood Inference, Springer, New York, 2001, p. 211). Our results complement those of Hu (Can. J. Stat. 25 (1997) 45). In particular, we invoke a different asymptotic paradigm than that in Hu (Can. J. Stat. 25 (1997) 45). Moreover, our adaptive weights are allowed to depend on the data.     

Model diagnostics for the proportional hazards model with length-biased data

Length-biased data are frequently encountered in prevalent cohort studies. Many statistical methods have been developed to estimate the covariate effects on the survival outcomes arising from such data while properly adjusting for length-biased sampling. Among them, regression methods based on the proportional hazards model have been widely adopted. However, little work has focused on checking the proportional hazards model assumptions with length-biased data, which is essential to ensure the validity of inference. In this article, we propose a statistical tool for testing the assumed functional form of covariates and the proportional hazards assumption graphically and analytically under the setting of length-biased sampling, through a general class of multiparameter stochastic processes. The finite sample performance is examined through simulation studies, and the proposed methods are illustrated with the data from a cohort study of dementia in Canada.

     

On minimum Hellinger distance estimation

Efficiency and robustness are two fundamental concepts in parametric estimation problems. It was long thought that there was an inherent contradiction between the aims of achieving robustness and efficiency; that is, a robust estimator could not be efficient and vice versa. It is now known that the minimum Hellinger distance approached introduced by Beran [R. Beran, Annals of Statistics 1977;5:445–463] is one way of reconciling the conflicting concepts of efficiency and robustness. For parametric models, it has been shown that minimum Hellinger estimators achieve efficiency at the model density and simultaneously have excellent robustness properties. In this article, we examine the application of this approach in two semiparametric models. In particular, we consider a two‐component mixture model and a two‐sample semiparametric model. In each case, we investigate minimum Hellinger distance estimators of finite‐dimensional Euclidean parameters of particular interest and study their basic asymptotic properties. Small sample properties of the proposed estimators are examined using a Monte Carlo study. The results can be extended to semiparametric models of general form as well. The Canadian Journal of Statistics 37: 514–533; 2009 © 2009 Statistical Society of Canada     

Mean squared error estimators of small area means using survey weights

Using survey weights, You & Rao [You and Rao, The Canadian Journal of Statistics 2002; 30, 431–439] proposed a pseudo‐empirical best linear unbiased prediction (pseudo‐EBLUP) estimator of a small area mean under a nested error linear regression model. This estimator borrows strength across areas through a linking model, and makes use of survey weights to ensure design consistency and preserve benchmarking property in the sense that the estimators add up to a reliable direct estimator of the mean of a large area covering the small areas. In this article, a second‐order approximation to the mean squared error (MSE) of the pseudo‐EBLUP estimator of a small area mean is derived. Using this approximation, an estimator of MSE that is nearly unbiased is derived; the MSE estimator of You & Rao [You and Rao, The Canadian Journal of Statistics 2002; 30, 431–439] ignored cross‐product terms in the MSE and hence it is biased. Empirical results on the performance of the proposed MSE estimator are also presented. The Canadian Journal of Statistics 38: 598–608; 2010 © 2010 Statistical Society of Canada