International Statistical Review Articles (Project Euclid)

A Statistical Approach to Assess Referendum Results: the Venezuelan Recall Referendum 2004

Thu, 05 Aug 2010 15:41 EDT

Maria M. Febres Cordero, Bernardo Márquez

Source: Internat. Statist. Rev., Volume 74, Number 3, 215--389.

Abstract:
This article presents a statistical approach to assess the coherence of official results of referendum processes. The statistical analysis described is divided in four phases, according to the methodology used and the corresponding results: (1) Initial Study, (2) Quantification of irregular certificates of election, (3) Identification of irregular voting centers and (4) Estimation of recall referendum results. The technique of cluster analysis is applied to address the issue of heterogeneity of the parishes with respect to their political preferences. The Venezuelan recall referendum 2004 is the case study we used to apply the proposed methodology, based on the data published by the ''Consejo Nacional Electoral'' (CNE-National Electoral Council). Finally, we present the conclusions of the study which we summarize as follows: The percentage of irregular certificates of election is between 22.2% and 26.5% of the total; 18% of the voting centers show an irregular voting pattern in their certificates of election, the votes corresponding to this irregularity are around 2,550,000; The result estimate, using the unbiased votes as representative of the population for the percentage of YES votes against President Chávez is 56.4% as opposed to the official result of 41% .

Comparison of Benchmarking Methods with and without a Survey Error Model

Thu, 05 Aug 2010 15:41 EDT

Zhao-Guo Chen, Ka Ho Wu

Source: Internat. Statist. Rev., Volume 74, Number 3, 285--304.

Abstract:
For a target socio-economic variable, two sources of data with different precisions and collecting frequencies may be available. Typically, the less frequent data (e.g., annual report or census) are more reliable and are considered as benchmarks. The process of using them to adjust the more frequent and less reliable data (e.g., repeated monthly surveys) is called benchmarking. In this paper, we show the relationship among three types of benchmarking methods in the literature, namely the Denton (original and modified), the regression, and the signal-extraction methods. A new method called ''quasi-linear regression'' is proposed under the multiplicative assumption. The numerical Denton method is currently widely used. The aim of this paper is to promote the other two methods which are statistically model-based; the model for the survey error is assumed to be known. Assuming the survey-error series follows an autoregressive model of order 1, by simulation, we investigate the impact of misspecification of the model on the benchmarking prediction according to the criterion of minimizing the root-mean-squared error of prediction. It is concluded that both statistical methods have great advantages over the Denton method and they are robust to misspecification of the survey-error model. The problem of how to obtain a survey-error model is also mentioned.

Causality and Causal Models: A Conceptual Perspective

Thu, 05 Aug 2010 15:41 EDT

Benito V. Frosini

Source: Internat. Statist. Rev., Volume 74, Number 3, 305--334.

Abstract:
This paper aims at displaying a synthetic view of the historical development and the current research concerning causal relationships, starting from the Aristotelian doctrine of causes, following with the main philosophical streams until the middle of the twentieth century, and commenting on the present intensive research work in the statistical domain. The philosophical survey dwells upon various concepts of cause, and some attempts towards picking out spurious causes. Concerning statistical modelling, factorial models and directed acyclic graphs are examined and compared. Special attention is devoted to randomization and pseudo-randomization (for observational studies) in view of avoiding the effect of possible confounders. An outline of the most common problems and pitfalls, encountered in modelling empirical data, closes the paper, with a warning to be very cautious in modelling and inferring conditional independence between variables. This paper is based on the President's Lecture, given at the Biennial Meeting of the Italian Statistical Society, Bari, June 2004.

Improving Statistics on International Migration in Asia

Thu, 05 Aug 2010 15:41 EDT

Graeme Hugo

Source: Internat. Statist. Rev., Volume 74, Number 3, 335--355.

Abstract:
International migration has reached unprecedented scale, diversity and political, economic, social and demographic significance in Asia over the last decade. Despite this data collection of migrant stocks and flows remains very limited in most Asian countries. Accordingly, policy making on migration in the region lacks an evidence base and is influenced by interest groups, anecdotal evidence and prejudice. This paper argues that the heightened security consciousness since 911 together with the development of efficient computer based collection and analysis of migration data systems has created a propitious environment for bringing about a parametric improvement in data collection on international migration in Asia. A number of suggestions are made in this regard, especially the inclusion of relevant international migration questions in the 2010 round of population censuses.

Towards an Integrated Statistical System at Statistics Netherlands

Thu, 05 Aug 2010 15:41 EDT

Nico Heerschap, Leon Willenborg

Source: Internat. Statist. Rev., Volume 74, Number 3, 357--378.

Abstract:
Changes in circumstances put pressure on Statistics Netherlands (SN) to redesign the way its statistics are produced. Key developments are: the changing needs of data-users, growing competition, pressure to reduce the survey burden on enterprises, emerging new technologies and methodologies and, first and foremost, the need for more efficiency because of budget cuts. This paper describes how SN, and especially its business statistics, can adapt to these new circumstances. We envisage an optimum situation as one with a single standardised production line for all statistics and a central data repository at its core. This single production line is supported by generic and standardised tools, metadata and workflow management. However, it is clear that such an optimum situation cannot be realised in just a few years. It should be seen as the point on the horizon. Therefore, we also describe the first transformation steps from the product-based stovepipe-oriented statistical process of the past to a more integrated process of the future. A similar modernisation process exists in the area of social statistics. In the near future both systems of business and social statistics are expected to connect at pivotal points and eventually converge on one overall business architecture for SN. Discussions about such an overall business architecture for SN have already been started and the first core projects have been set up.

Measure for Measure: Exact F Tests and the Mixed Models Controversy

Thu, 05 Aug 2010 15:41 EDT

Viviana B. Lencina, Julio M. Singer

Source: Internat. Statist. Rev., Volume 74, Number 3, 391--402.

Abstract:
We consider exact F tests for the hypothesis of null random factor effect in the presence of interaction under the two factor mixed models involved in the mixed models controversy. We show that under the constrained parameter ( CP ) model, even in unbalanced data situations, MSB/MSE (in the usual ANOVA notation) follows an exact F distribution when the null hypothesis holds. We also obtain an exact F test for what is generally (and erroneously) assumed to be an equivalent hypothesis under the unconstrained parameter ( UP ) model. For unbalanced data, such a corresponding test statistic does not coincide with MSB/MSAB (the test statistic advocated for balanced data cases). We compute the power of the exact test under different imbalance patterns and show that although the loss of power increases with the degree of imbalance, it still remains reasonable from a practical point of view.

Estimation in Two-Stage Models with Heteroscedasticity

Thu, 05 Aug 2010 15:41 EDT

John Buonaccorsi

Source: Internat. Statist. Rev., Volume 74, Number 3, 403--418.

Abstract:
A surprising number of important problems can be cast in the framework of estimating a mean and variance using data arising from a two-stage structure. The first stage is a random sampling of ''units'' with some quantity of interest associated with the unit. The second stage produces an estimate of that quantity and usually, but not always, an estimated standard error, which may change considerably across units. Heteroscedasticity in the estimates over different units can arise for a number of reasons, including variation associated with the unit and changing sampling effort over units. This paper presents a broad discussion of the problem of making inferences for the population mean and variance associated with the unobserved true values at the first stage of sampling. A careful discussion of the causes of heteroscedasticity is given, followed by an examination of ways in which inferences can be carried out in a manner that is robust to the nature of the within unit heteroscedasticity. Among the conclusions are that under any type of heteroscedasticity, an unbiased estimate of the mean and the variance of the estimated mean can be obtained by using the estimates as if they were true unobserved values from the first stage. The issue of using the mean versus a weighted average which tries to account for the heteroscedasticity is also discussed. An unbiased estimate of the population variance is given and the variance of this estimate and its covariance with the estimated mean is provided under various types of heteroscedasticity. The two-stage setting arises in many contexts including the one-way random effects models with replication, meta-analysis, multi-stage sampling from finite populations and random coefficients models. We will motivate and illustrate the problem with data arising from these various contexts with the goal of providing a unified framework for addressing such problems.