{"title":"Replication and Evidence Factors in Observational Studies Paul R. Rosenbaum Chapman & Hall/CRC, 2021, xviii + 254 pages, $120, hardback ISBN: 978-036748-388-3","authors":"John H. Maindonald","doi":"10.1111/insr.12495","DOIUrl":"10.1111/insr.12495","url":null,"abstract":"","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48012945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fundamentals of Causal Inference with R Babette A. Brumback Chapman & Hall/CRC, 2021, xi + 236 pages, $69.95, hardcover ISBN: 978-0-3677-0505-3","authors":"Debashis Ghosh","doi":"10.1111/insr.12494","DOIUrl":"10.1111/insr.12494","url":null,"abstract":"","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48182731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Practical Smoothing: The Joys of P-splines Paul H. C. Eilers and Brian D. MarxCambridge University Press, 2021, xii + 199 pages, $59.99, hardcover ISBN: 978-1-1084-8295-0","authors":"Krzysztof Podgórski","doi":"10.1111/insr.12497","DOIUrl":"10.1111/insr.12497","url":null,"abstract":"","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47192305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Herbert Susmann, Monica Alexander, Leontine Alkema
{"title":"Temporal Models for Demographic and Global Health Outcomes in Multiple Populations: Introducing a New Framework to Review and Standardise Documentation of Model Assumptions and Facilitate Model Comparison","authors":"Herbert Susmann, Monica Alexander, Leontine Alkema","doi":"10.1111/insr.12491","DOIUrl":"10.1111/insr.12491","url":null,"abstract":"<p>There is growing interest in producing estimates of demographic and global health indicators in populations with limited data. Statistical models are needed to combine data from multiple data sources into estimates and projections with uncertainty. Diverse modelling approaches have been applied to this problem, making comparisons between models difficult. We propose a model class, Temporal Models for Multiple Populations (TMMPs), to facilitate both documentation of model assumptions in a standardised way and comparison across models. The class makes a distinction between the process model, which describes latent trends in the indicator interest, and the data model, which describes the data generating process of the observed data. We provide a general notation for the process model that encompasses many popular temporal modelling techniques, and we show how existing models for a variety of indicators can be written using this notation. We end with a discussion of outstanding questions and future directions.</p>","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9790657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10833470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Survey Weighting after Imperfect Linkage to an Administrative File","authors":"James Chipperfield","doi":"10.1111/insr.12490","DOIUrl":"10.1111/insr.12490","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper proposes an instrumental variable regression estimator of population totals using a sample, a set of links between the sample units and records on an administrative file, and a set of calibration totals calculated from the administrative file. This paper proposes a survey-weighted estimator of a population total that is valid when the survey non-response mechanism is non-ignorable and false negatives occur in the administrative-survey linkage. False negatives lead to measurement error in the administrative variables that are available on the survey and will lead to biased estimates if not taken into account. We show the benefit of the proposed approach in a simulation and in a case study.</p>\u0000 </div>","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46636355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Interview with John M. Abowd","authors":"Ian Schmutte, Lars Vilhuber","doi":"10.1111/insr.12489","DOIUrl":"10.1111/insr.12489","url":null,"abstract":"<div>\u0000 \u0000 <p>John M. Abowd is the Chief Scientist and Associate Director for Research and Methodology, US Census Bureau. He completed his AB in Economics at Notre Dame in 1973 and his PhD in Economics at University of Chicago in 1977 under Arnold Zellner. During his academic career, John has held faculty positions at Princeton, the University of Chicago, and, since 1987 at Cornell University where he is the Edmund Ezra Day Professor Emeritus of Economics, Statistics and Data Science. John was trained as a statistician and labor economist, and his economic research has focused on the rigorous empirical evaluation of labor market institutions. In the late 1990s, he began working with the Census Bureau on projects that would end up leveraging administrative and survey records into official statistical products. Through that work, he has developed a research agenda focused on issues necessary to generate those products, including data privacy, synthetic data, total error analysis, data linkage, and missing data problems, among others.</p>\u0000 </div>","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44248370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eduarda T. C. Chagas, Marcelo Queiroz-Oliveira, Osvaldo A. Rosso, Heitor S. Ramos, Cristopher G. S. Freitas, Alejandro C. Frery
{"title":"White Noise Test from Ordinal Patterns in the Entropy–Complexity Plane","authors":"Eduarda T. C. Chagas, Marcelo Queiroz-Oliveira, Osvaldo A. Rosso, Heitor S. Ramos, Cristopher G. S. Freitas, Alejandro C. Frery","doi":"10.1111/insr.12487","DOIUrl":"10.1111/insr.12487","url":null,"abstract":"<div>\u0000 \u0000 <p>This article serves two purposes. Firstly, it surveys the Bandt and Pompe methodology for the statistical community, stressing topics that are open for research. Secondly, it contributes towards a better understanding of the statistical properties of that approach for time series analysis. The Bandt and Pompe methodology consists of computing information theory descriptors from the histogram of ordinal patterns. Such descriptors lie in a 2D manifold: the entropy–complexity plane. This article provides the first proposal of a test in the entropy–complexity plane for the white noise hypothesis. Our test is based on true white noise sequences obtained from physical devices. The proposed methodology provides consistent results: It assesses sequences of true random samples as random (adequate test size), rejects correlated and contaminated sequences (sound test power) and captures the randomness of generators previously analysed in the literature.</p>\u0000 </div>","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47001423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unlucky Number 13? Manipulating Evidence Subject to Snooping","authors":"Uwe Hassler, Marc-Oliver Pohle","doi":"10.1111/insr.12488","DOIUrl":"10.1111/insr.12488","url":null,"abstract":"<p>Questionable research practices have generated considerable recent interest throughout and beyond the scientific community. We subsume such practices involving secret data snooping that influences subsequent statistical inference under the term MESSing (manipulating evidence subject to snooping) and discuss, illustrate and quantify the possibly dramatic effects of several forms of MESSing using an empirical and a simple theoretical example. The empirical example uses numbers from the most popular German lottery, which seem to suggest that 13 is an unlucky number.</p>","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/insr.12488","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46993654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ray Chambers, Stephen Beare, Scott Peak, Mohammed Al-Kalbani
{"title":"Nudging a Pseudo-Science Towards a Science—The Role of Statistics in a Rainfall Enhancement Trial in Oman","authors":"Ray Chambers, Stephen Beare, Scott Peak, Mohammed Al-Kalbani","doi":"10.1111/insr.12486","DOIUrl":"10.1111/insr.12486","url":null,"abstract":"<div>\u0000 \u0000 <p>Although cloud seeding is a commonly used and plausible method for rainfall enhancement, its practical efficacy has not been established for seeding of convective clouds with hygroscopic materials. Other methods of rainfall enhancement are viewed as much less plausible. Thus, although increased electrical charge has been shown to enhance precipitation in cloud chamber experiments, exactly how ionisation of clouds can increase rainfall in the open atmosphere remains conjectural. A trial of the efficacy of ionisation for rainfall enhancement in the Hajar Mountains of Oman was carried out over 2013–2018. This paper provides some background to this non-mainstream approach to increasing rainfall, showing how statistical modelling of rainfall data might be used to nudge rainfall enhancement via ionisation towards a more scientifically acceptable status. Analysis of the data collected in the trial shows that ionisation led to a statistically significant enhancement in positive rainfall in gauges located up to 70 km downwind of the ionisers. A headline analysis specified prior to commencement of the trial resulted in an estimate of 16.23% enhancement relative to rainfall that would have fallen without any ionisation, while a more sophisticated after the event analysis increased this estimate to 17.64%.</p>\u0000 </div>","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47200463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}