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This article reviews Albert Einstein's first published paper, submitted for publication in 1900. At that time, Einstein was 21 and a recent college graduate. His paper uses modeling and least squares to analyze data in support of a scientific proposition. Einstein is shown to be well trained, for his day, in using statistics as a tool in his scientific research. This paper also shows his ability to make trivial arithmetic mistakes and some clumsiness in data recording. A major aim of this article is to help provide a better appreciation of Einstein as an active user of statistical arguments in this and other of his important publications. [ABSTRACT FROM AUTHOR]

Dissemination of ideas from theory to practice is a significant challenge in statistics. Quick identification of articles useful to practitioners would greatly assist in this dissemination, thereby improving science. This article uses the citation count history of articles to identify key papers from 1985 to 2002 from 12 statistics journals for applied biostatisticians. One feature requiring attention in order to appropriately rank an article's impact is assessment of the citation accrual patterns over time. Citation counts in statistics differ dramatically from fields such as medicine. In statistics, most articles receive few citations, with 15-year-old articles from five key journals receiving a median of 13 citations compared to 66 in the Journal of Clinical Oncology. However, statistics articles in the top 2%-3% continue to gain citations at a high rate past 15 years, exceeding those in JCO, whose counts slow dramatically around 8 years past publication. Articles with the highest expected applied uses 20 years post publication were identified using joinpoint regression. In this evaluation, the fraction of citations that represent applied use was defined and estimated. The false discovery rate, quantification of heterogeneity in meta-analysis, and generalized estimating equations rank as the ideas with the greatest estimated applied impact. [ABSTRACT FROM AUTHOR]

The paper referred to is ‘The Future of Data Analysis,’ published in 1962. Many authors have discussed it, notably Peter Huber, who in 1995 reviewed the period starting with Hotelling's 1940 article ‘The Teaching of Statistics.’ I extend the scope of Huber's remarks by considering also the period before 1940 and developments since 1995. I ask whether statistics is a science and suggest that to attract bright students to our subject, we need to show them the excitement and rewards of applied work. [ABSTRACT FROM AUTHOR]

Reproducibility, the ability to reproduce the results of published papers or studies using their computer code and data, is a cornerstone of reliable scientific methodology. Studies where results cannot be reproduced by the scientific community should be treated with caution. Over the past decade, the importance of reproducible research has been frequently stressed in a wide range of scientific journals such as Nature and Science and international magazines such as The Economist. However, multiple studies have demonstrated that scientific results are often not reproducible across research areas such as psychology and medicine. Statistics, the science concerned with developing and studying methods for collecting, analyzing, interpreting and presenting empirical data, prides itself on its openness when it comes to sharing both computer code and data. In this article, we examine reproducibility in the field of statistics by attempting to reproduce the results in 93 published papers in prominent journals using functional magnetic resonance imaging (fMRI) data during the 2010–2021 period. Overall, from both the computer code and the data perspective, among all the 93 examined papers, we could only reproduce the results in 14 (15.1%) papers, that is, the papers provide both executable computer code (or software) with the real fMRI data, and our results matched the results in the paper. Finally, we conclude with some author-specific and journal-specific recommendations to improve the research reproducibility in statistics. [ABSTRACT FROM AUTHOR]

In many collegiate level statistics courses, the focus of the learning outcomes is often on the analysis of data after it has been collected. Students are provided with clean data sets from previous studies to practice statistical analysis, but receive little to no application as to the amount of time and effort that goes in to collecting good data. To account for these deficits at the author's institution, a design of experiments course was created that provided students with a more hands-on learning experience to the statistical process, especially as pertains to data collection. This paper focuses on five of the experiments that students designed and implemented during the course, and some suggestions to instructors that may wish to use these experiments in their own courses. [ABSTRACT FROM AUTHOR]

The Cash statistic, also known as the C statistic, is commonly used for the analysis of low-count Poisson data, including data with null counts for certain values of the independent variable. The use of this statistic is especially attractive for low-count data that cannot be combined, or re-binned, without loss of resolution. This paper presents a new maximum-likelihood solution for the best-fit parameters of a linear model using the Poisson-based Cash statistic. The solution presented in this paper provides a new and simple method to measure the best-fit parameters of a linear model for any Poisson-based data, including data with null counts. In particular, the method enforces the requirement that the best-fit linear model be non-negative throughout the support of the independent variable. The method is summarized in a simple algorithm to fit Poisson counting data of any size and counting rate with a linear model, by-passing entirely the use of the traditional χ 2 statistic. [ABSTRACT FROM AUTHOR]

In order to improve the effect of agricultural data mining and statistics in the Internet era, based on data mining technology, this paper combines data mining technology with modern agricultural information to solve the problems of poor timeliness and incomplete information in the collection and sorting of agricultural information. Moreover, this paper makes innovations in time series representation and time series measurement, and uses custom methods to improve agricultural data mining and statistical algorithms. In addition, this paper finds reasonable mining methods to acquire knowledge through data analysis. Finally, this paper combines the actual needs to construct a data mining and statistical analysis model of precision and intelligent agriculture based on big data analysis, and designs experiments to verify the performance of the model. The research results show that the model constructed in this paper has a certain effect. [ABSTRACT FROM AUTHOR]

Researchers in statistical shape analysis often analyze outlines of objects. Even though these contours are infinite-dimensional in theory, they must be discretized in practice. When discretizing, it is important to reduce the number of sampling points considerably to reduce computational costs, but to not use too few points so as to result in too much approximation error. Unfortunately, determining the minimum number of points needed to achieve sufficiently approximate the contours is computationally expensive. In this paper, we fit regression models to predict these lower bounds using characteristics of the contours that are computationally cheap as predictor variables. However, least squares regression is inadequate for this task because it treats overestimation and underestimation equally, but underestimation of lower bounds is far more serious. Instead, to fit the models, we use the LINEX loss function, which allows us to penalize underestimation at an exponential rate while penalizing overestimation only linearly. We present a novel approach to select the shape parameter of the loss function and tools for analyzing how well the model fits the data. Through validation methods, we show that the LINEX models work well for reducing the underestimation for the lower bounds. [ABSTRACT FROM AUTHOR]

It is essential to develop infrared (IR) thermogram identification technologies to establish automatic diagnosis systems in power substations. The convolutional neural network (CNN) based methods show the highest accuracy in this field. The IR thermograms of electrical equipment are very different from general digital images, which means the present methods need further improvements. For data-driven CNN methods, it is necessary to study the characteristics of the IR data. This paper collected 11817 thermograms from substations and structured the dataset according to equipment types. The statistical features of mean, variance, skewness, kurtosis and contrast are analyzed and compared with other five image datasets. Several tricks are revealed from the analysis and tested on CNN models. Firstly, greycaling the Iron pseudo-color images extracts the temperature information and makes it possible to design models with fewer channels. The test shows it could reduce over 35% computational costs. Secondly, the sparse information of color and edges of thermograms makes it necessary to keep the original aspect ratio. The image preprocessing method of cropping shows better performance than padding and rescaling. Thirdly, the 0-1 normalization can boost the training process for about 100 epochs, which is related to the particular background of thermograms. [ABSTRACT FROM AUTHOR]

This paper presents a machine-learning-based method for evaluating the internal value of talent in any organization and for evaluating the salary criteria. The study assumes the design and development of a salary predictor, based on artificial intelligence technologies, to help determine the internal value of employees and guarantee internal equity in the organization. The aim of the study is to achieve internal equity, which is a critical element a that directly affects employees' motivation. We implemented and validated the method with 130 employees and more than 70 talent acquisition cases with a Basque technology research organization during the years 2021 and 2022. The proposed method is based on statistical data assessment and machine-learning-based regression. We found that while most organizations have established variables for job evaluation as well as salary increments for staff according to their contribution to the organization, only a few employ tools to support equitable internal compensation. This study presents a successful real case of artificial intelligence applications where machine learning techniques help managers make the most equitable and least biased salary decisions possible, based on data. [ABSTRACT FROM AUTHOR]

In this paper, we consider the dynamical behaviour of a stochastic coronavirus (COVID-19) susceptible-infected-removed epidemic model with the inclusion of the influence of information intervention and Lévy noise. The existence and uniqueness of the model positive solution are proved. Then, we establish a stochastic threshold as a sufficient condition for the extinction and persistence in mean of the disease. Based on the available COVID-19 data, the parameters of the model were estimated and we fit the model with real statistics. Finally, numerical simulations are presented to support our theoretical results. [ABSTRACT FROM AUTHOR]

This paper presents a statistical analysis of the actual mean material properties for typical grades of concrete and reinforcement available in Australia. The analysis was performed using a database of 3,447 concrete cylinder test results and 15,201 reinforcement tensile test results. The test results were taken over a period from 2009 to 2021. The paper provides a summary of the mean values and respective coefficient of variation values for the different grades of concrete and reinforcement that make up the database. Distinctive manufacturing trends and variability between suppliers were observed for reinforcement samples and appropriate recommendations have been proposed. Researchers or designers can adopt these values to undertake probabilistic assessments of RC structures. The paper also provides recommendations for mean material properties for the purpose of undertaking non-linear analysis of RC structures. The database of test results also includes early age strength data for concrete, which have been used to provide recommendations for predicting the early age strength of various standard grades of concrete available in Australia. The paper also presents an assessment of the theoretical characteristic values from the database for the various grades of reinforcement and concrete and how they compare to respective specified code requirements. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the mean change-point models based on associated sequences. Under some weak conditions, we obtain a limit distribution of CUSUM statistic which can be used to judge the mean change-mount δ n is satisfied or dissatisfied n 1 / 2 δ n = o (1). We also study the consistency of sample covariances and change-point location statistics. Based on Normality and Lognormality data, some simulations such as empirical sizes, empirical powers and convergence are presented to test our results. As an important application, we use CUSUM statistics to do the mean change-point analysis for a financial series. [ABSTRACT FROM AUTHOR]

The C statistic, also known as the Cash statistic, is often used in astronomy for the analysis of low-count Poisson data. The main advantage of this statistic, compared to the more commonly used χ 2 statistic, is its applicability without the need to combine data points. This feature has made the C statistic a very useful method to analyze Poisson data that have small (or even null) counts in each resolution element. One of the challenges of the C statistic is that its probability distribution, under the null hypothesis that the data follow a parent model, is not known exactly. This paper presents an effort towards improving our understanding of the C statistic by studying (a) the distribution of C statistic for a fully specified model, (b) the distribution of Cmin resulting from a maximum-likelihood fit to a simple one-parameter constant model, i.e. a model that represents the sample mean of N Poisson measurements, and (c) the distribution of the associated Δ C statistic that is used for parameter estimation. The results confirm the expectation that, in the high-count limit, both C statistic and Cmin have the same mean and variance as a χ 2 statistic with same number of degrees of freedom. It is also found that, in the low-count regime, the expectation of the C statistic and Cmin can be substantially lower than for a χ 2 distribution. The paper makes use of recent X-ray observations of the astronomical source PG 1116+215 to illustrate the application of the C statistic to Poisson data. [ABSTRACT FROM AUTHOR]

The Journal of Statistics and Data Science Education regularly publishes interviews with notable statistics and data science educators. These interviews aim to provide insight into the development of statistics and data science education, offer a historical perspective, and humanize the field through personal anecdotes. Allan Rossman has been conducting these interviews since 2011, profiling a diverse range of individuals who have made significant contributions to the field. Taylor & Francis has made the complete set of interviews easily accessible through centralized lists. The current issue of the journal features papers on various topics, including the role of eugenics in the development of statistics and strategies for addressing this history in the classroom. [Extracted from the article]

Rapid population growth has had a significant impact on society, economy and environment, which will challenge the achievement of the United Nations Sustainable Development Goals (SDGs). Spatially accurate and detailed population distribution data are essential for measuring the impact of population growth and tracking progress on the SDGs. However, most population data are evenly distributed within administrative units, which seriously lacks spatial details. There are scale differences between the population statistical data and geospatial data, which makes data analysis and needed research difficult. The disaggregation method is an effective way to obtain the spatial distribution of population with greater granularity. It can also transform the statistical population data from irregular administrative units into regular grids to characterize the spatial distribution of the population, and the original population count is preserved. This paper summarizes the research advances of population disaggregation in terms of methodology, ancillary data, and products and discusses the role of spatial disaggregation of population statistical data in monitoring and evaluating SDG indicators. Furthermore, future work is proposed from two perspectives: challenges with spatial disaggregation and disaggregated population as an Essential SDG Variable (ESDGV). [ABSTRACT FROM AUTHOR]

Europe has experienced a major boom of new breweries over the last thirty years, with thousands of new breweries being set up, even in regions where brewing has no history. So far, however, this microbrewing wave has not been systematically mapped. This paper presents a unique database of European breweries from 1990–2020. Using a series of maps and statistical analyses, it shows how breweries have gradually spread across Europe. Initially, microbreweries were being established in countries that are in a declining stage of the beer life-cycle from industrial breweries. After 2005 (and particularly in the 2010s), breweries reached other regions through neighbouring and hierarchical spatial diffusion. [ABSTRACT FROM AUTHOR]

A special source of difficulty in the statistical analysis is the possibility that some subjects may not have a complete observation of the response variable. Such incomplete observation of the response variable is called censoring. Censorship can occur for a variety of reasons, including limitations of measurement equipment, design of the experiment, and non-occurrence of the event of interest until the end of the study. In the presence of censoring, the dependence of the response variable on the explanatory variables can be explored through regression analysis. In this paper, we propose to examine the censorship problem in context of the class of asymmetric, i.e., we have proposed a linear regression model with censored responses based on skew scale mixtures of normal distributions. We develop a Monte Carlo EM (MCEM) algorithm to perform maximum likelihood inference of the parameters in the proposed linear censored regression models with skew scale mixtures of normal distributions. The MCEM algorithm has been discussed with an emphasis on the skew-normal, skew Student-t-normal, skew-slash and skew-contaminated normal distributions. To examine the performance of the proposed method, we present some simulation studies and analyze a real dataset. [ABSTRACT FROM AUTHOR]

The Journal of Statistics and Data Science Education special issue on "Computing in the Statistics and Data Science Curriculum "features a set of papers that provide amosaic of curricular innovations and approaches that embrace computing. As we reviewed the papers we felt that this collection would benefit from the perspective of the authors of the landmark "Computing in the Statistics Curricula" (TAS 2010) paper. We asked Deb and Duncan to take this opportunity to reflect on the landscape when they wrote the paper, to comment on the current situation, and to speculate on the future. [ABSTRACT FROM AUTHOR]

Although statistical literacy has become a key competence in today's data-driven society, it is usually not a part of statistics education. To address this issue, we propose an innovative concept for a conference-like seminar on the topic of statistical literacy. This seminar draws attention to the relevance and importance of statistical literacy, and moreover, students are made aware of the process of science communication and are introduced to the peer review process for the assessment of scientific papers. In the summer term 2020, the seminar was conducted as a joint project by the University of Hamburg, the University of Muenster, and the Joachim Herz Foundation. In this article, we present the concept of the seminar and our experience with this concept in the summer term 2020. [ABSTRACT FROM AUTHOR]

Dispersion indexes with respect to the Poisson and binomial distributions are widely used to assess the conformity of the underlying distribution from an observed sample of the count with one or the other of these theoretical distributions. Recently, the exponential variation index has been proposed as an extension to nonnegative continuous data. This paper aims to gather to study the unified definition of these indexes with respect to the relative variability of a nonnegative natural exponential family of distributions through its variance function. We establish the strong consistency of the plug-in estimators of the indexes as well as their asymptotic normalities. Since the exact distributions of the estimators are not available in closed form, we consider the test of hypothesis relying on these estimators as test statistics with their asymptotic distributions. Simulation studies globally suggest good behaviours of these tests of hypothesis procedures. Applicable examples are analysed, including the lesser-known references such as negative binomial and inverse Gaussian, and improving the very usual case of the Poisson dispersion index. Concluding remarks are made with suggestions of possible extensions. [ABSTRACT FROM AUTHOR]

Application of the exact statistical inference frequently leads to non-standard probability distributions of the considered estimators or test statistics. The exact distributions of many estimators and test statistics can be specified by their characteristic functions, as is the case for the null distribution of the Bartlett's test statistic. However, analytical inversion of the characteristic function, if possible, frequently leads to complicated expressions for computing the distribution function and the corresponding quantiles. An efficient alternative is the well-known method based on numerical inversion of the characteristic functions, which is, however, ignored in popular statistical software packages. In this paper, we present the explicit characteristic function of the corrected Bartlett's test statistic together with the computationally fast and efficient implementation of the approach based on numerical inversion of this characteristic function, suggested for evaluating the exact null distribution used for testing homogeneity of variances in several normal populations, with possibly unequal sample sizes. [ABSTRACT FROM AUTHOR]

Deciding on the best statistical method to apply when the response variable is ordinal is essential because the way the categories are ordered in the data is relevant as it could change the results of the analysis. Although the models for continuous variables have similarities to those for ordinal variables, this paper presents the advantages of the use of the ordering information on the outcomes with methods developed for modeling ordinal data such as the ordered stereotype model. The novelty of this article lies in showing the dangers of assigning equally spaced scores to ordered response categories in statistical analysis, which are illustrated with a simulation study and a case study. We propose a new way to use the score parameters, which incorporates the fitted spacing dictated by the data. Additionally, this article uses score parameter estimates in the ordered stereotype model to propose a new measure to calculate continuous medians in the raw data: the adjusted c-median. It benefits the general audience who can easily understand the median as a summary statistic. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

This paper introduces a new two-parameter exponentiated discrete Lindley distribution. A wide range of its structural properties are investigated. This includes the shape of the probability mass function, hazard rate function, moments, skewness, kurtosis, stress–strength reliability, mean residual lifetime, mean past lifetime, order statistics and L-moment statistics. The hazard rate function can be increasing, decreasing, decreasing–increasing–decreasing, increasing–decreasing–increasing, unimodal, bathtub, and J-shaped depending on its parameters values. Two methods are used herein to estimate the model parameters, namely, the maximum likelihood, and the proportion. A detailed simulation study is carried out to examine the bias and mean square error of maximum likelihood and proportion estimators. The flexibility of the proposed model is explained by using four distinctive data sets. It can serve as an alternative model to other lifetime distributions in the existing statistical literature for modeling positive real data in many areas. [ABSTRACT FROM AUTHOR]

It should, however, be noted that such approximations have ultimately allowed the authors to conduct a comprehensive analysis of thousands of images from multiple studies, which further substantiates their findings. We congratulate the authors on an interesting paper which combines the ideas of shape analysis with longitudinal data analysis. This, of course, loses some of the elegance of the SRNF framework, but at a considerable ease of preserving the topology of the data and avoiding Euclidean approximations. [Extracted from the article]

We often encounter situations in which data from the TCGA that have been analyzed in papers we read or reviewed cannot be reproduced, even when TCGA datasets are used, especially in survival analyses. Therefore, we attempted to confirm the data source for TCGA survival analysis and found that several websites used to analyze the survival data of TCGA datasets inappropriately handle the survival data, causing differences in statistical analyses. This causes the misinterpretation of results because figures of survival analysis results in several papers are sometimes exactly as generated by these sites, and the results depend on only the tools provided by these sites. We would like to make this situation widely known and raise the problem for scientific soundness. [ABSTRACT FROM AUTHOR]

The trafficking of cocaine has become a global challenge now and Ghana is no exception. Cocaine is a whitish powder, which is, produced both from natural and synthetic means. This paper studied the metal content of seized cocaine in Ghana and the data used for batch identification. Ten metals, namely, Pb, Cu, Mg, Mn, Cr, As, Ni, Fe, Co and Ca were analyzed in 37 samples which were sampled from 2010 to 2014. Analyses of the metals were done using ICP-MS and data was analyzed using statistical tools. The results showed that, calcium recorded the highest amount in all the samples with a mean of 64.94mg/kg followed by Magnesium, Zinc and Iron with mean values of 24.35mg/kg, 6.25mg/kg and 2.65mg/kg, respectively. All the samples, within-seizure classification under class A showed to significant differences between each pair at a confidence level of 95%. With three sample pairs under class B in the within-seizure classification, one of the pairs; 103A and 105B showed no significant differences between them even though they were sampled from two different packages from the same seizure. Five samples from five different seizures also showed a significant difference among them showing that they came from different batches or origin. It is confirmed that seized cocaine contained poisonous heavy metals like Lead, Arsenic and Chromium, which have the amount that could affect the user-provide figures. Based on the data gathered from the within-seizure class A group, it could be proposed that a missing cocaine could be identified by its metal content. [ABSTRACT FROM AUTHOR]

Background and purpose: Studies of education and learning that were described as experiments have been carried out in the USA by educational psychologists since about 1900. In this paper, we discuss the history of randomised trials in education in the USA in terms of five historical periods. In each period, the use of randomised trials was motivated by the research interests and conditions of the era. We have characterised these periods in terms of decades with sharp boundaries as a convenience. Sources of evidence and main arguments: Although some of the early studies used random allocation (and even random allocation of clusters such as schools), early researchers did not clearly understand the role of randomisation or clearly distinguish it from methods such as alternation. In 1940, E. F. Lindquist published an important book whose goal was to translate R. A. Fisher’s ideas into language congenial to education researchers, but this had little impact on education research outside of psychology. There was a substantial increase in the number of randomised trials during the period from 1960 to 1980, as the US government enacted and evaluated a variety of social programmes. This was followed by a dramatic decrease during the period from 1980 to 2000, amid debates about the relevance of randomised trials in education research. The creation of the US Institute of Education Sciences in 2002 provided major financial and administrative support for randomised trials, which has led to a large number of trials being conducted since that time. Conclusions: These developments suggest that there is a promising future for randomised trials in the USA. American education scientists must remain committed to explaining why evidence from randomised field trials has an indispensable role to play in making wise decisions about education policy and advancing our capacity to improve education for a productive workforce and a successful society. [ABSTRACT FROM AUTHOR]

We agree that converting data to similar resolutions would lose some statistical information from our data. We thank gratefully Professors Wei Tu, Bei Jiang, Linglong Kong, and Professor Sudipto Banerjee for their insightful comments and discussion of our paper. The inference of the occupancy status of houses sharing one location might require more information at the individual level, which is the primary data barrier in social science. [Extracted from the article]

In these cases getting accurate confidence intervals is of first order importance, and the methods Ignatiadis and Wager develop are likely to be useful. I want to congratulate Nikolaos Ignatiadis and Stefan Wager on a very stimulating paper on a timely and important topic. [Extracted from the article]

In many of statistical theory of asymptotic distribution, it is based on normal distribution or some parameters that it is difficult to determine. In this paper we consider combined Poisson distribution and introduce one of the theoretical approach that does not require much of them to obtain more convenience, instead by using inequality of best estimate. [ABSTRACT FROM AUTHOR]

In this paper, we review some results for insurance risk theory. We first introduce a variety of the insurance risk models proposed thus far. Then, we show that the expected discounted penalty function (the so-called Gerber-Shiu function) can describe some risk indicators. Next, the dividend problem is discussed; more precisely, the (approximated) optimal dividend barrier is derived and other extended dividend strategies introduced. In addition, some modified models depending on reinsurance or tax are introduced. Finally, we discuss the statistical estimation of the ruin probability and the Gerber-Shiu function. [ABSTRACT FROM AUTHOR]

The article comments on the research paper "Basic statistical considerations for occupational and environmental physiology: the Temperature toolbox" by A. R. Caldwell and S. N. Cheuvront in the current issue of the journal. Topics include the paper goes without saying that experimental design, data collection, data analysis, and dissemination of results are important and their review being a guide for physiologists to avoid common pitfalls and mistakes as they plan and analyze their studies.

The following three articles are the results of papers presented and discussed at a symposium entitled "Improving the Workforce of the Future: Opportunities in Undergraduate Education," held August 12-13, 2000, in Indianapolis, IN. This symposium was sponsored by the American Statistical Association through its Undergraduate Statistics Education Initiative. The first article was the keynote address at the symposium. The latter two articles are position papers that were developed in part through discussions among representatives from liberal arts colleges, research universities, industry, and government at a May 1999 meeting at the ASA Headquarters and a subsequent April 2000 workshop in Alexandria, VA. This workshop was partially supported by the National Science Foundation. Other position papers based on symposium discussions are being developed and are scheduled to appear in the Journal of Statistical Education. [ABSTRACT FROM AUTHOR]

Background: Intersectoral perspectives of health are present in the rhetoric of the sustainable development goals. Yet its descriptions of systematic approaches for an intersectoral monitoring vision, joining determinants of health, and barriers or facilitators to accessing healthcare services are lacking. Objective: To explore models of associations between health outcomes and health service coverage, and health determinants and health systems responsiveness, and thereby to contribute to monitoring, analysis, and assessment approaches informed by an intersectoral vision of health. Design: The study is designed as a series of ecological, cross-country regression analyses, covering between 23 and 57 countries with dependent health variables concentrated on the years 2002-2003. Countries cover a range of development contexts. Health outcome and health service coverage dependent variables were derived from World Health Organization (WHO) information sources. Predictor variables representing determinants are derived from the WHO and World Bank databases; variables used for health systems' responsiveness are derived from the WHO World Health Survey. Responsiveness is a measure of acceptability of health services to the population, complementing financial health protection. Results: Health determinants' indicators -- access to improved drinking sources, accountability, and average years of schooling -- were statistically significant in particular health outcome regressions. Statistically significant coefficients were more common for mortality rate regressions than for coverage rate regressions. Responsiveness was systematically associated with poorer health and health service coverage. With respect to levels of inequality in health, the indicator of responsiveness problems experienced by the unhealthy poor groups in the population was statistically significant for regressions on measles vaccination inequalities between rich and poor. For the broader determinants, the Gini mattered most for inequalities in child mortality; education mattered more for inequalities in births attended by skilled personnel. Conclusions: This paper adds to the literature on comparative health systems research. National and international health monitoring frameworks need to incorporate indicators on trends in and impacts of other policy sectors on health. This will empower the health sector to carry out public health practices that promote health and health equity. [ABSTRACT FROM AUTHOR]

In this paper we are concerned with inferences from a sample survey to a finite population. We contrast inferences that are dependent on an assumed model with inferences based on the randomization induced by the sample selection plan. Randomization consistency for finite population estimators is defined and adopted as a requirement of probability sampling. A numerical example is examined to illustrate the dangers in the use of model-dependent estimators even when the model is apparently consonant with the sample data. The paper concludes with a summary of principles that we believe should guide the practitioner of sample surveys of finite populations. [ABSTRACT FROM AUTHOR]

In this article, the author comments on the research paper of John J. Wiorkowski titled "Estimating Volumes of Remaining Fossil Fuel Resources: A Critical Review," published in the September 1981 issue of "Journal of the American Statistical Association." According to the author, the strength of Wiorkowski's paper is in bringing the important problem of petroleum resource estimation to the attention of statisticians. The major weaknesses are in the organization and classification of models and the gaps in coverage. The major issues in resource estimation that Wiorkowski discusses are models for estimating the total oil and gas remaining to be found and a closely related problem, estimating the amount of appreciation in known fields. The problem with the discussion of the models is the lack of a proper classification scheme. Although Wiorkowski mentions the model of researchers E. Barouch and G.M. Kaufman, he fails to note that it is one of a general class of models that are based on the discovery process and fails to emphasize that it is a play model, whereas the others he discusses are used at a higher level of aggregation.

The article presents the author's comments on paper by researcher D. Basu related to randomization analysis of experimental data. Basu writes entertainingly, perhaps, but not informatively. Basu's paper discusses prerandomization, postrandomization, and unrecorded randomization. This discussion is irrelevant. But it is useful, perhaps, to make a remark. It also discusses the sufficiency principle. As Basu has written, this is a data-reduction principle. Basu also discusses researcher R.A. Fisher randomization test. It is obvious that the population in a randomization test of a randomized experiment is "the product of the statistician's imagination." With respect to Basu's writing on "the physical act of randomization," the author believes Basu is merely plain wrong. The paper also describes randomized pair trial. In his paper, Basu gives a hypothetical interchange of a statistician and a scientist and the author. The author suggests that this serves no useful purpose. The author finds the lack of knowledge that underlies Basu's thesis rather surprising, incongruous, and deplorable.

The author is pleased to discuss a paper on the estimation of probability density functions and the location of bumps. There is an extensive literature on density estimation, but many statisticians seem doubtful about the usefulness of these techniques because their application seems subjective and complicated. A major criticism the author would make of this paper is that it does not help to dispel this negative attitude of statisticians toward density estimation. One cannot help but be impressed by the ingenuity of I. J. Good and R. A. Gaskins and even to believe that they may be able to successfully fit probability densities to data. The existence of bumps at the extremes of a sample can be investigated for large sample sizes by treating the bottom and top ends of the original sample as two new samples to be analyzed by themselves. Statistical scientists should heed the flippant advice of Sir Arthur Eddington: "Never trust an experimental result until it has been confirmed by theory."

This paper focuses on a regionalization attempt to partly solve data limitation problems in statistical analysis of high flows to derive discharge–duration–frequency (QDF) relationships. The analysis is based on 24 selected catchments in the Lake Victoria Basin (LVB) in East Africa. Characteristics of the theoretical QDF relationships were parameterized to capture their slopes of extreme value distributions (evd), tail behaviour and scaling measures. To enable QDF estimates to be obtained for ungauged catchments, interdependence relationships between the QDF parameters were identified, and regional regression models were developed to explain the regional difference in these parameters from physiographic characteristics. In validation of the regression models, from the lowest (5 years) to the highest (25 years) return periods considered, the percentage bias in the QDF estimates ranged from –2% for the 5-year return period to 27% for 25-year return period.Editor D. Koutsoyiannis [ABSTRACT FROM AUTHOR]

Background: Family planning expansion has been identified as an impetus to harnessing Nigeria's demographic dividend. However, there is a need for data to address pockets of inequality and to better understand cultural and social factors affecting contraceptive use and health benefits. This paper contributes to addressing these needs by providing evidence on the trends and sub-national patterns of modern contraceptive prevalence in Nigeria and the association between contraceptive use and high-risk births in Nigeria. Design: The study utilised women's data from the last three Demographic and Health Surveys (2003, 2008, and 2013) in Nigeria. The analysis involved descriptive, bivariate, and multivariate analyses. The multivariate analyses were performed to examine the relationship between high-risk births and contraceptive use. Associations were examined using Poisson regression. Results: Findings showed that respondents in avoidable high-risk birth categories were less likely to use contraceptives compared to those at no risk [rate ratio 0.82, confidence interval: 0.76-0.89, p <0.001]. Education and wealth index consistently predicted significant differences in contraceptive use across the models. Conclusions:. The results of this study suggest that women in the high-risk birth categories were significantly less likely to use a modern method of contraception relative to those categorised as having no risk. However, there are huge sub-national variations at regional and state levels in contraceptive prevalence and subsequent high-risk births. These results further strengthen evidence-based justification for increased investments in family planning programmes at the state and regional levels, particularly regions and states with high unmet needs for family planning. [ABSTRACT FROM AUTHOR]

Background: Worldwide, there is an increased reliance on casual staff in the health sector. Recent policy attention in South Africa has focused on the interrelated challenges of agency nursing and moonlighting in the health sector. Objective: This paper examines the potential health system consequences of agency nursing and moonlighting among South African nurses. Methods: During 2010, a cluster random sample of 80 hospitals was selected in four South African provinces. On the survey day, all nurses providing clinical care completed a self-administered questionnaire after giving informed consent. The questionnaire obtained information on socio-demographics, involvement in agency nursing and moonlighting, and self-reported indicators of potential health system consequences of agency nursing and moonlighting. A weighted analysis was done using STATA® 13. Results: In the survey, 40.7% of nurses reported moonlighting or working for an agency in the preceding year. Of all participants, 51.5% reported feeling too tired to work, 11.5% paid less attention to nursing work on duty, and 10.9% took sick leave when not actually sick in the preceding year. Among the moonlighters, 11.9% had taken vacation leave to do agency work or moonlighting, and 9.8% reported conflicting schedules between their primary and secondary jobs. In the bivariate analysis, moonlighting nurses were significantly more likely than non-moonlighters to take sick leave when not sick (p=0.011) and to pay less attention to nursing work on duty (p=0.035). However, in a multiple logistic regression analysis, the differences between moonlighters and non-moonlighters did not remain statistically significant after adjusting for other sociodemographic variables. Conclusion: Although moonlighting did not emerge as a statistically significant predictor, the reported health system consequences are serious. A combination of strong nursing leadership, effective management, and consultation with and buy-in from front-line nurses is needed to counteract the potential negative health system consequences of agency nursing and moonlighting. [ABSTRACT FROM AUTHOR]

Increasing integration and availability of data on large groups of persons has been accompanied by proliferation of statistical and other algorithmic prediction tools in banking, insurance, marketing, medicine, and other fields (see, e.g., Steyerberg 2009a, b). Controversy may ensue when such tools are introduced to fields traditionally reliant on individual clinical evaluations. Such controversy has arisen about "actuarial" assessments of violence recidivism risk, that is, the probability that someone found to have committed a violent act will commit another during a specified period. Recently, Hart, Michie, and Cooke (2007a) and subsequent papers from these authors in several reputable journals have claimed to demonstrate that statistical assessments of such risks are inherently too imprecise to be useful, using arguments that would seem to apply to statistical risk prediction quite broadly. This commentary examines these arguments from a technical statistical perspective, and finds them seriously mistaken in many particulars. They should play no role in reasoned discussions of violence recidivism risk assessment. [ABSTRACT FROM AUTHOR]

The article focuses on the study regarding the boundary of smoothing parameter space in statistical analysis. It mentions several papers by different authors which featured different approaches and methods to determine smoothing parameters on the edge of the feasible parameter space. It also describes the proposed fixes of the researchers that offer substantial improvement to the phase transition to smooth estimates to nonzero smoothing penalty.

Objective. The main objective of this paper is to investigate whether incorporating an electronic optional guideline tool (EOGT) in the standardized referral template used by general practitioners (GPs) when referring patients to specialized care can improve outpatient referral appropriateness. Design. Intervention study with an intervention and a control group. Setting. 210 GPs in the municipality of Bergen and the Department of Thoracic Medicine at Haukeland University Hospital. Subjects. 2400 patients referred to the Department of Thoracic Medicine at Haukeland University Hospital. Results. An electronic optional guideline tool (EOGT) was implemented on 93 of 210 GPs' computer systems. The referral quality and the time spent reviewing each referral were evaluated by the hospital specialists. The GPs did not know that their referrals were being evaluated. The specialists were blinded with regard to information concerning the intervention and the control group. The specialists reported significantly higher referral quality and considerably less time spent on evaluating referrals when using the EOGT, with an overall time reduction of 34%. Likewise, GPs also reported that the EOGT was easy to use, time-saving and led to an improved quality of their referrals. Conclusion. This study documents an improvement in the quality of the referrals. Since the GPs save time by using the EOGT, there is no reason to believe that they will discontinue using it. In fact, the tool may be even more beneficial for the GP. The authors believe that it is possible to implement the EOGT as a standard referral tool within various fields of medicine and are currently in the process of developing these tools. [ABSTRACT FROM AUTHOR]

The article presents the winners of the 2005 "Technometrics" prizes. Daniel Pena won the 2005 Jack Youden Prize for Best Expository Paper for his article "A new statistic for influence in linear regression". German Molina, M.J. Bayarri and James O. Berger won the 2005 Frank Wilcoxon Prize for Best Practical Application Paper for their article "Statistical inverse analysis for a network microsimulator". A list of past winners of "Technometrics" prizes from 1969 to 2004 is presented.

This article comments on a paper by Nozer D. Singpurwalla and Jane M. Booker which aimed to develop a line of argument that demonstrates that probability theory has a sufficiently rich structure for incorporating fuzzy sets within its framework. Google reports about 670,000 websites that connect with the phrase fuzzy logic. From a mathematical perspective, the concept of a fuzzy set is somewhat disconcerting, because a fuzzy set is generally not a set, but rather a variable. A crucial issue, which was debated already in the earliest days of fuzzy logic, concerns whether or not membership values are just probabilities in disguise. Certainly, the original motivating examples deal primarily with formalizing variables that correspond to natural language concepts that are in everyday use. The paper's section 4 introduces Lofti Zadeh's rejection of the law of the excluded middle, with reference to differentiating between membership values and probabilities. The commenter's reading of the paper's section 4, and of formula (1) in particular, suggests that Zadeh in 1968 might well have approved a solution along the lines of the preceding paragraph, except that he would have used the posterior expectation of m(x) as a summary of the posterior distribution.

This article comments on a paper by Nozer D. Singpurwalla and Jane M. Booker which aimed to develop a line of argument that probability theory has a sufficiently rich structure tor incorporating fuzzy sets within its framework. According to the commenter, the paper provides a real advance in the understanding of fuzzy sets, by providing a sensible connection between membership functions and likelihood, and thereby probability. He says the paper's modification of the basic question is answered most convincingly. However, the answer raises an apparent conflict between the two calculi of fuzzy logic and probability. What is now needed is a second article to resolve this conflict. The commenter's conjecture is that the resolution will show that the rules of fuzzy logic are untenable. According to him, his principal reason behind the conjecture is that the rules of the probability calculus follow from simple, obvious assumptions, whereas those of the fuzzy calculus have been arbitrarily selected. He points out that this arbitrariness is fine for a pure mathematician. But, according to him, an applied mathematician, faced with the reality of uncertainty in the real world, must take into account that world and cannot ignore the basic assumptions about uncertainty that underlie the probability calculus and reflect basic truths about the world.

Background: Well-working health information systems are considered vital with the quality of health data ranked of highest importance for decision making at patient care and policy levels. In particular, health facilities play an important role, since they are not only the entry point for the national health information system but also use health data (and primarily) for patient care. Design: A multiple case study was carried out between March and August 2012 at the antenatal care (ANC) clinics of two private and one public Kenyan hospital to describe clinical information systems and assess the quality of information. The following methods were developed and employed in an iterative process: workplace walkthroughs, structured and in-depth interviews with staff members, and a quantitative assessment of data quality (completeness and accurate transmission of clinical information and reports in ANC).Views of staff and management on the quality of employed information systems, data quality, and influencing factors were captured qualitatively. Results: Staff rated the quality of information higher in the private hospitals employing computers than in the public hospital which relies on paper forms. Several potential threats to data quality were reported. Limitations in data quality were common at all study sites including wrong test results, missing registers, and inconsistencies in reports. Feedback was seldom on content or quality of reports and usage of data beyond individual patient care was low. Conclusions: We argue that the limited data quality has to be seen in the broader perspective of the information systems in which it is produced and used. The combination of different methods has proven to be useful for this. To improve the effectiveness and capabilities of these systems, combined measures are needed which include technical and organizational aspects (e.g. regular feedback to health workers) and individual skills and motivation. [ABSTRACT FROM AUTHOR]