bluuebunny/crossref_metadata_2025_split huggingface dataset:
Article
Authors: STEWART AA , RUSH B , DAVIS E 
Published: August 2010

ObjectiveTo document the efficacy of intratumoural injections of 5‐fluorouracil for the treatment of equine sarcoids.DesignA prospective study that included 13 horses and one donkey.ProcedureSarcoids were confirmed by histological examination and treated with intratumoural 5‐fluorouracil every 2 weeks. If the sarcoids did not resolve after seven treatments, treatment was considered a failure. All cases were re‐examined 6 months after treatment commenced and owners were telephoned 3 years after commencement of treatment to report on tumour recurrence. Outcome comparisons were performed to determine the effect of previous treatment, tumour size and tumour location on sarcoid resolution. The efficacy of intratumoural 5‐fluorouracil was compared with other previously documented treatments of equine sarcoids.ResultsSarcoids smaller than 13.5 cm3were significantly (P=0.032) more likely to resolve with treatment than larger sarcoids. Sarcoids that were not responsive to previous therapies were significantly (P = 0.007) more likely to recur after 3 years than sarcoids that had not been treated prior to this study. In this study, there were similar rates of resolution in cases with mutiple tumours (66.6%) when compared to cases with single tumours (60%). The numbers in this study were too small to properly evaluate the effect of tumour location on the success of treatment. Intratumoural 5‐fluorouracil appeared to have resolved sarcoids in 9 of 13 cases (61.5%) as determined by follow up conversation with the owners 3 years after the initial treatment.ConclusionThe use of intratumoural 5‐fluorouracil compares favourably with other treatment modalities for sarcoids, with a long term successful resolution rate of 61.5%. Owners should be warned that resistant sarcoids and sarcoids larger than 13.5 cm have a poorer prognosis for resolution and more aggressive therapeutic options should be considered.
Profiling training preparation in young Australian Thoroughbred racehorses
Authors: Cogger N , Perkins N , Hodgson DR , Reid SW , Evans DL 
Published: August 2010

Objective  To describe the impact of age, sex, and musculoskeletal (MS) injury on three preparation‐level measures of performance: (i) the duration of preparation, (ii) time from the beginning of the preparation until the first start in a race or barrier trial, and (iii) time from the first start until the end of the preparation.Methods  Daily training and injury data for 2‐ and 3‐year old Thoroughbred racehorses were collected fortnightly from 14 trainers in NSW, Australia. Training data were aggregated into units referred to as ‘preparations’. Univariate and multivariate analytical methods were used to examine the associations between the explanatory variables and each of the measures of performance.Results  There were 1274 preparations recorded in 451 horses. Younger horses had a shorter interval from the first start in a race or barrier trial to the end of the preparation. MS injury was not conditionally associated with any of the outcomes.Conclusion  MS injuries in young racehorses have limited impact on long‐term performance, although care must be taken in interpreting the results because they could be confounded by variables not considered in this analysis. This study also begins to unravel the complicated relationship between age and previous exposure to training, with results supporting the hypothesis that the intensity of training increases with increasing age.
ICT Statistics at the New Millennium—Developing Official Statistics—Measuring the Diffusion of ICT and its Impact
Authors: Jeskanen‐Sundström Heli 
Published: August 2010

Summary The paper gives a short and very rough overview of the ongoing work in the field of statistics relating to the development of information and communication technology (ICT) and its impacts on the economies and on the society as a whole. It introduces three slightly different approaches with different emphasis on describing the emergence and diffusion of ICT and the respective economic and social change. These are termed the indicators approach, the new economy approach and the intellectual capital approach. The paper also discusses the basic requirements for the establishment of a new statistical system, as well as the present obstacles and problems of this work. Finally, some remarks are presented regarding further statistical co‐operation in this field.
Development in Information and Communications Technology (ICT) Statistics at the Australian Bureau of Statistics
Authors: Power Tim 
Published: August 2010

Summary This paper outlines the ICT statistical developments that the ABS has undertaken over recent years. These developments have been on both the supply side (ICT industry) and the demand side (use of IT by sector). The content of ABS ICT surveys has changed significantly over the last few years and are expected to develop further in line with industry changes and emerging policy needs. Recent developments in household collections have been the inclusion of IT use questions in the 2001 Census of Population and Housing and in various ABS social surveys such as Children's Participation in Culture and Leisure Activities. Annual business IT use surveys are now conducted and include topics such as Internet commerce and IT security. Biennial ICT industry surveys are conducted to provide data on ICT production, imports and exports, ICT industry employment, performance and structure information. An Internet activity survey is run every six months and provides regional Internet access details and infrastructure details on Internet service providers. A major development for 2002–03 will be the compilation of an ICT satellite account. ABS intends to produce an ICT Information Development Plan to guide its future statistical development work in the ICT field.
The Language of the English Biometric School
Authors: Aldrich John 
Published: August 2010

SummaryThis paper considers the language devised by Karl Pearson and his associates for discussing distributions, populations and samples, the basic language for frequentist inference. The original language—some of which is still in use—is described and also the changes it underwent under the influence of R.A. Fisher and of Russian and American mathematicians. The period covered is roughly 1890–1950.
Covariate Measurement Error in Quadratic Regression
Authors: Kuha Jouni , Temple Jonathan 
Published: August 2010

SummaryWe consider quadratic regression models where the explanatory variable is measured with error. The effect of classical measurement error is to flatten the curvature of the estimated function. The effect on the observed turning point depends on the location of the true turning point relative to the population mean of the true predictor. Two methods for adjusting parameter estimates for the measurement error are compared. First, two versions of regression calibration estimation are considered. This approximates the model between the observed variables using the moments of the true explanatory variable given its surrogate measurement. For certain models an expanded regression calibration approximation is exact. The second approach uses moment‐based methods which require no assumptions about the distribution of the covariates measured with error. The estimates are compared in a simulation study, and used to examine the sensitivity to measurement error in models relating income inequality to the level of economic development. The simulations indicate that the expanded regression calibration estimator dominates the other estimators when its distributional assumptions are satisfied. When they fail, a small‐sample modification of the method‐of‐moments estimator performs best. Both estimators are sensitive to misspecification of the measurement error model.
Hierarchical Models in Environmental Science
Authors: Wikle Christopher K. 
Published: August 2010

SummaryEnvironmental systems are complicated. They include very intricate spatio‐temporal processes, interacting on a wide variety of scales. There is increasingly vast amounts of data for such processes from geographical information systems, remote sensing platforms, monitoring networks, and computer models. In addition, often there is a great variety of scientific knowledge available for such systems, from partial differential equations based on first principles to panel surveys. It is argued that it is not generally adequate to consider such processes from a joint perspective. Instead, the processes often must be considered as a coherently linked system of conditional models. This paper provides a brief overview of hierarchical approaches applied to environmental processes. The key elements of such models can be considered in three general stages, the data stage, process stage, and parameter stage. In each stage, complicated dependence structure is mitigated by conditioning. For example, the data stage can incorporate measurement errors as well as multiple datasets with varying supports. The process and parameter stages can allow spatial and spatio‐temporal processes as well as the direct inclusion of scientific knowledge. The paper concludes with a discussion of some outstanding problems in hierarchical modelling of environmental systems, including the need for new collaboration approaches.
Sequential Data Assimilation Techniques in Oceanography
Authors: Bertino Laurent , Evensen Geir , Wackernagel Hans 
Published: August 2010

SummaryWe review recent developments of sequential data assimilation techniques used in oceanography to integrate spatio‐temporal observations into numerical models describing physical and ecological dynamics. Theoretical aspects from the simple case of linear dynamics to the general case of nonlinear dynamics are described from a geostatistical point‐of‐view. Current methods derived from the Kalman filter are presented from the least complex to the most general and perspectives for nonlinear estimation by sequential importance resampling filters are discussed. Furthermore an extension of the ensemble Kalman filter to transformed Gaussian variables is presented and illustrated using a simplified ecological model. The described methods are designed for predicting over geographical regions using a high spatial resolution under the practical constraint of keeping computing time sufficiently low to obtain the prediction before the fact. Therefore the paper focuses on widely used and computationally efficient methods.
Interpreting DNA Evidence: A Review
Authors: Foreman L.A. , Champod C. , Evett I.W. , Lambert J.A. , Pope S. 
Published: August 2010

SummaryThe paper provides a review of current issues relating to the use of DNA profiling in forensic science. A short historical section gives the main statistical milestones that occurred during a rapid development of DNA technology and operational uses. Greater detail is then provided for interpretation issues involving STR DNA profiles, including:– methods that take account of population substructure in DNA calculations;– parallel work carried out by the US National Research Council;– the move away from multiple independence testing in favour of experiments that demonstrate the robustness of casework procedures;– the questionable practice of source attribution ‘with reasonable scientific certainty’;– the effect on the interpretation of profiles obtained under increasingly sensitive techniques, the LCN technique in particular;– the use of DNA profiles as an intelligence tool;– the interpretation of DNA mixtures.Experience of presenting DNA evidence within UK courts is also discussed. The paper then summarises a generic interpretation framework based on the concept of likelihood ratio within a hierarchy of propositions. Finally the use of Bayesian networks to interpret DNA evidence is reviewed.
Copyright Damages and Statistics
Authors: Basmann Robert L. , Slottje Daniel J. 
Published: August 2010

Summary This paper discusses the statistical issues that arise in conducting an economic damages analysis in the context of a litigation matter involving copyrights. Calculating damages in copyright cases turns out to be a natural application for econometric modelling methods. Surprisingly, elementary statistical issues can be a source of significant debate between the experts in such matters. In this paper, we present a case study and illustrate how issues such as interpretation of p‐values and what “rejection of the null hypothesis” really “means” in such matters.
Statistical Issues Arising in Disparate Impact Cases and the Use of the Expectancy Curve in Assessing the Validity of Pre‐Employment Tests
Authors: Gastwirth Joseph L. , Miao Weiwen , Zheng Gang 
Published: August 2010

SummaryDisparate impact cases concern the potential adverse effect seemingly neutral employment practices, such as passing a pre‐employment test or possessing a fixed level of education, have on minority applicants. Their purpose is to eliminate discrimination by subterfuge, i.e., imposing a requirement that eliminates many minority individuals who could do the job but who do not meet the requirement. When a significantly higher fraction of applicants from minority groups fail the requirement compared to majority applicants, the requirement needs to be shown to be job‐related. Statistical techniques used at the various stages of a disparate impact claim are described. Properties of the expectancy curve, which describes the utility of a pre‐employment test and helps in defining a band of scores defining “equivalently skilled” applicants are discussed.
Using the Lee–Carter Method to Forecast Mortality for Populations with Limited Data*
Authors: Li Nan , Lee Ronald , Tuljapurkar Shripad 
Published: August 2010

Summary The Lee–Carter method for modeling and forecasting mortality has been shown to work quite well given long time series of data. Here we consider how it can be used when there are few observations at uneven intervals. Assuming that the underlying model is correct and that the mortality index follows a random walk with drift, we find the method can be used with sparse data. The central forecast depends mainly on the first and last observation, and so can be generated with just two observations, preferably not too close in time. With three data points, uncertainty can also be estimated, although such estimates of uncertainty are themselves highly uncertain and improve with additional observations. We apply the methods to China and South Korea, which have 3 and 20 data points, respectively, at uneven intervals.
Toward a New Model for Probabilistic Household Forecasts
Authors: Leiwen Jiang , O'Neill Brian C. 
Published: August 2010

Summary Household projections are key components of analyses of several issues of social concern, including the welfare of the elderly, housing, and environmentally significant consumption patterns. Researchers or policy makers that use such projections need appropriate representations of uncertainty in order to inform their analyses. However, the weaknesses of the traditional approach of providing alternative variants to single “best guess” projection are magnified in household projections, which have many output variables of interest, and many input variables beyond fertility, mortality, and migration. We review current methods of household projections and the potential for using them to produce probabilistic projections, which would address many of these weaknesses. We then propose a new framework for a household projection method of intermediate complexity that we believe is a good candidate for providing a basis for further development of probabilistic household projections. An extension of the traditional headship rate approach, this method is based on modelling changes in headship rates decomposed by household size as a function of variables describing demographic events such as parity specific fertility, union formation and dissolution, and leaving home. It has moderate data requirements, manageable complexity, allows for direct specification of demographic events, and produces output that includes the most important household characteristics for many applications. An illustration of how such a model might be constructed, using data on the U.S. and China over the past several decades, demonstrates the viability of the approach.
Assumptions on Fertility in Stochastic Population Forecasts*
Authors: Alders Maarten , de Beer Joop 
Published: August 2010

Summary In recent years Statistics Netherlands has published several stochastic population forecasts. The degree of uncertainty of the future population is assessed on the basis of assumptions about the probability distribution of future fertility, mortality and migration. The assumptions on fertility are based on an analysis of historic forecasts of the total fertility rate (TFR), on time‐series models of observations of the TFR, and on expert knowledge. This latter argument‐based approach refers to the TFR distinguished by birth order. In the most recent Dutch forecast the 95% forecast interval of the total fertility rate in 2050 is assumed to range from 1.2 to 2.3 children per woman.
Probabilistic Population Projections for India with Explicit Consideration of the Education‐Fertility Link
Authors: Lutz Wolfgang , Scherbov Sergei 
Published: August 2010

Summary Among the different sources of uncertainty in population forecasting, uncertain changes in the structure of heterogeneous populations have received little attention so far, although they can have significant impacts. Here we focus on the effect of changes in the educational composition of the population on the overall fertility of the population in the presence of strong fertility differentials by education. With data from India we show that alternative paths of future female enrolment in education result in significantly different total fertility rates (TFR) for the country over the coming decades, even assuming identical fertility trends within each education group. These results from multi‐state population projections by education are then translated into a fully probabilistic population projection for India in which the results of alternative education scenarios are assumed to expand the uncertainty range of the future TFR in the total population. This first attempt to endogenize structural change with respect to education—which is the greatest measurable source of fertility heterogeneity in Asia—has resulted from a larger exercise of the Asian MetaCentre for Population and Sustainable Development Analysis to collect empirical information, scientific arguments as well as informed opinions about likely future population trends in Asia from a large number of population experts in the region. In this process, future changes in the educational composition of the population have been identified as a key driver of future fertility. The actual probabilistic population projections for India show that with high certainty, the Indian population will continue to grow to about 1.3 billion over the next quarter of a century. After that the uncertainty will get much wider, ranging from a continued strong increase to the beginning of a population decline in India.
Estimation of the Option Prime: Microsimulation of Backward Stochastic Differential Equations
Authors: Allende Héctor , Elías Carlos , Torres Soledad 
Published: August 2010

Summary A mathematical statistical model is needed to obtain an option prime and create a hedging strategy. With formulas derived from stochastic differential equations, the primes for US Dollar/Chilean Pesos currency options using a prime calculator are obtained. Furthermore, a backward simulation of the option prime trajectory is used with a numerical method created for backward stochastic differential equations. The use of statistics in finance is highly important in order to develop complex products.
An Appraisal and Bibliography of Tests for Multivariate Normality
Authors: Mecklin Christopher J. , Mundfrom Daniel J. 
Published: August 2010

SummaryThis paper is a review of many of the dozens of procedures currently available for testing a data set for goodness‐of‐fit to the multivariate normal distribution. A majority of the procedures can be placed into one of four basic categories. Most procedures are multivariate extensions or adaptations of procedures used for testing univariate normality. Results of several power studies are summarized, and an extensive bibliography of literature pertaining to testing for multivariate normality is provided.
Developing Official Stochastic Population Forecasts at the US Census Bureau
Authors: Long John F. , Hollmann Frederick W. 
Published: August 2010

Summary The U.S. Census Bureau is approaching a critical decision regarding a major facet of its methodology for forecasting the United States population. In the past, it has relied on alternative scenarios, low, medium, and high, to reflect varying interpretations of current trends in fertility, mortality, and international migration to forecast population. This approach has limitations that have been noted in the recent literature on population forecasting. Census Bureau researchers are embarking on an attempt to incorporate probabilistic reasoning to forecast prediction intervals around point forecasts to future dates. The current literature offers a choice of approaches to this problem. We are opting to employ formal time series modeling of parameters of fertility, mortality, and international migration, with stochastic renewal processes. The endeavor is complicated by the administrative necessity to produce a large amount of racial and Hispanic origin detail in the population, as well as the ubiquitous cross‐categories of age and sex. As official population forecasts must meet user demand, we are faced with the added challenge of presenting and supporting the resulting product in a way that is comprehensible to users, many of whom have little or no comprehension of the technical forecasting literature, and are accustomed to simple, deterministic answers. We may well find a need to modify our strategy, depending on the realities that may emerge from the limitations of data, the administrative requirements of the product, and the diverse needs of our user community.
Causality: a Statistical View
Authors: Cox D.R. , Wermuth Nanny 
Published: August 2010

SummaryStatistical aspects of causality are reviewed in simple form and the impact of recent work discussed. Three distinct notions of causality are set out and implications for densities and for linear dependencies explained. The importance of appreciating the possibility of effect modifiers is stressed, be they intermediate variables, background variables or unobserved confounders. In many contexts the issue of unobserved confounders is salient. The difficulties of interpretation when there are joint effects are discussed and possible modifications of analysis explained. The dangers of uncritical conditioning and marginalization over intermediate response variables are set out and some of the problems of generalizing conclusions to populations and individuals explained. In general terms the importance of search for possibly causal variables is stressed but the need for caution is emphasized.
Parametric Inference for Diffusion Processes Observed at Discrete Points in Time: a Survey
Authors: Sørensen Helle 
Published: August 2010

Summary This paper is a survey of estimation techniques for stationary and ergodic diffusion processes observed at discrete points in time. The reader is introduced to the following techniques: (i) estimating functions with special emphasis on martingale estimating functions and so‐called simple estimating functions; (ii) analytical and numerical approximations of the likelihood function which can in principle be made arbitrarily accurate; (iii) Bayesian analysis and MCMC methods; and (iv) indirect inference and EMM which both introduce auxiliary (but wrong) models and correct for the implied bias by simulation.