The Development of the MRC Statistical Unit, 1911-1948
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School of Social Sciences Economics Division University of Southampton Southampton SO17 1BJ, UK Discussion Papers in Economics and Econometrics Mathematics in the Statistical Society 1883-1933 John Aldrich No. 0919 This paper is available on our website http://www.southampton.ac.uk/socsci/economics/research/papers ISSN 0966-4246 Mathematics in the Statistical Society 1883-1933* John Aldrich Economics Division School of Social Sciences University of Southampton Southampton SO17 1BJ UK e-mail: [email protected] Abstract This paper considers the place of mathematical methods based on probability in the work of the London (later Royal) Statistical Society in the half-century 1883-1933. The end-points are chosen because mathematical work started to appear regularly in 1883 and 1933 saw the formation of the Industrial and Agricultural Research Section– to promote these particular applications was to encourage mathematical methods. In the period three movements are distinguished, associated with major figures in the history of mathematical statistics–F. Y. Edgeworth, Karl Pearson and R. A. Fisher. The first two movements were based on the conviction that the use of mathematical methods could transform the way the Society did its traditional work in economic/social statistics while the third movement was associated with an enlargement in the scope of statistics. The study tries to synthesise research based on the Society’s archives with research on the wider history of statistics. Key names : Arthur Bowley, F. Y. Edgeworth, R. A. Fisher, Egon Pearson, Karl Pearson, Ernest Snow, John Wishart, G. Udny Yule. Keywords : History of Statistics, Royal Statistical Society, mathematical methods. -
History of the Development of the ICD
History of the development of the ICD 1. Early history Sir George Knibbs, the eminent Australian statistician, credited François Bossier de Lacroix (1706-1777), better known as Sauvages, with the first attempt to classify diseases systematically (10). Sauvages' comprehensive treatise was published under the title Nosologia methodica. A contemporary of Sauvages was the great methodologist Linnaeus (1707-1778), one of whose treatises was entitled Genera morborum. At the beginning of the 19th century, the classification of disease in most general use was one by William Cullen (1710-1790), of Edinburgh, which was published in 1785 under the title Synopsis nosologiae methodicae. For all practical purposes, however, the statistical study of disease began a century earlier with the work of John Graunt on the London Bills of Mortality. The kind of classification envisaged by this pioneer is exemplified by his attempt to estimate the proportion of liveborn children who died before reaching the age of six years, no records of age at death being available. He took all deaths classed as thrush, convulsions, rickets, teeth and worms, abortives, chrysomes, infants, livergrown, and overlaid and added to them half the deaths classed as smallpox, swinepox, measles, and worms without convulsions. Despite the crudity of this classification his estimate of a 36 % mortality before the age of six years appears from later evidence to have been a good one. While three centuries have contributed something to the scientific accuracy of disease classification, there are many who doubt the usefulness of attempts to compile statistics of disease, or even causes of death, because of the difficulties of classification. -
Bayesian Inference for Heterogeneous Event Counts
Bayesian Inference for Heterogeneous Event Counts ANDREW D. MARTIN Washington University This article presents an integrated set of Bayesian tools one can use to model hetero- geneous event counts. While models for event count cross sections are now widely used, little has been written about how to model counts when contextual factors introduce heterogeneity. The author begins with a discussion of Bayesian cross-sectional count models and discusses an alternative model for counts with overdispersion. To illustrate the Bayesian framework, the author fits the model to the number of women’s rights cosponsorships for each member of the 83rd to 102nd House of Representatives. The model is generalized to allow for contextual heterogeneity. The hierarchical model allows one to explicitly model contextual factors and test alternative contextual explana- tions, even with a small number of contextual units. The author compares the estimates from this model with traditional approaches and discusses software one can use to easily implement these Bayesian models with little start-up cost. Keywords: event count; Markov chain Monte Carlo; hierarchical Bayes; multilevel models; BUGS INTRODUCTION Heterogeneity is what makes society and, for that matter, statistics interesting. However, until recently, little attention has been paidto modeling count data observed in heterogeneous clusters (a notable exception is Sampson, Raudenbush, and Earls 1997). Explanations AUTHOR’S NOTE: This research is supported by the National Science Foundation Law and Social Sciences and Methodology, Measurement, and Statistics Sections, Grant SES-0135855 to Washing- ton University. I would like to thank Dave Peterson, Kevin Quinn, and Kyle Saunders for their helpful comments. I am particularly indebted to Christina Wolbrecht for sharing her valuable data set with me. -
Orme) Wilberforce (Albert) Raymond Blackburn (Alexander Bell
Copyrights sought (Albert) Basil (Orme) Wilberforce (Albert) Raymond Blackburn (Alexander Bell) Filson Young (Alexander) Forbes Hendry (Alexander) Frederick Whyte (Alfred Hubert) Roy Fedden (Alfred) Alistair Cooke (Alfred) Guy Garrod (Alfred) James Hawkey (Archibald) Berkeley Milne (Archibald) David Stirling (Archibald) Havergal Downes-Shaw (Arthur) Berriedale Keith (Arthur) Beverley Baxter (Arthur) Cecil Tyrrell Beck (Arthur) Clive Morrison-Bell (Arthur) Hugh (Elsdale) Molson (Arthur) Mervyn Stockwood (Arthur) Paul Boissier, Harrow Heraldry Committee & Harrow School (Arthur) Trevor Dawson (Arwyn) Lynn Ungoed-Thomas (Basil Arthur) John Peto (Basil) Kingsley Martin (Basil) Kingsley Martin (Basil) Kingsley Martin & New Statesman (Borlasse Elward) Wyndham Childs (Cecil Frederick) Nevil Macready (Cecil George) Graham Hayman (Charles Edward) Howard Vincent (Charles Henry) Collins Baker (Charles) Alexander Harris (Charles) Cyril Clarke (Charles) Edgar Wood (Charles) Edward Troup (Charles) Frederick (Howard) Gough (Charles) Michael Duff (Charles) Philip Fothergill (Charles) Philip Fothergill, Liberal National Organisation, N-E Warwickshire Liberal Association & Rt Hon Charles Albert McCurdy (Charles) Vernon (Oldfield) Bartlett (Charles) Vernon (Oldfield) Bartlett & World Review of Reviews (Claude) Nigel (Byam) Davies (Claude) Nigel (Byam) Davies (Colin) Mark Patrick (Crwfurd) Wilfrid Griffin Eady (Cyril) Berkeley Ormerod (Cyril) Desmond Keeling (Cyril) George Toogood (Cyril) Kenneth Bird (David) Euan Wallace (Davies) Evan Bedford (Denis Duncan) -
Statistics Making an Impact
John Pullinger J. R. Statist. Soc. A (2013) 176, Part 4, pp. 819–839 Statistics making an impact John Pullinger House of Commons Library, London, UK [The address of the President, delivered to The Royal Statistical Society on Wednesday, June 26th, 2013] Summary. Statistics provides a special kind of understanding that enables well-informed deci- sions. As citizens and consumers we are faced with an array of choices. Statistics can help us to choose well. Our statistical brains need to be nurtured: we can all learn and practise some simple rules of statistical thinking. To understand how statistics can play a bigger part in our lives today we can draw inspiration from the founders of the Royal Statistical Society. Although in today’s world the information landscape is confused, there is an opportunity for statistics that is there to be seized.This calls for us to celebrate the discipline of statistics, to show confidence in our profession, to use statistics in the public interest and to champion statistical education. The Royal Statistical Society has a vital role to play. Keywords: Chartered Statistician; Citizenship; Economic growth; Evidence; ‘getstats’; Justice; Open data; Public good; The state; Wise choices 1. Introduction Dictionaries trace the source of the word statistics from the Latin ‘status’, the state, to the Italian ‘statista’, one skilled in statecraft, and on to the German ‘Statistik’, the science dealing with data about the condition of a state or community. The Oxford English Dictionary brings ‘statistics’ into English in 1787. Florence Nightingale held that ‘the thoughts and purpose of the Deity are only to be discovered by the statistical study of natural phenomena:::the application of the results of such study [is] the religious duty of man’ (Pearson, 1924). -
The Scientific Rationality of Early Statistics, 1833–1877
The Scientific Rationality of Early Statistics, 1833–1877 Yasuhiro Okazawa St Catharine’s College This dissertation is submitted for the degree of Doctor of Philosophy. November 2018 Declaration Declaration This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except as declared in the Preface and specified in the text. It is not substantially the same as any that I have submitted, or, is being concurrently submitted for a degree or diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared in the Preface and specified in the text. I further state that no substantial part of my dissertation has already been submitted, or, is being concurrently submitted for any such degree, diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared in the Preface and specified in the text It does not exceed the prescribed word limit of 80,000 words for the Degree Committee of the Faculty of History. Yasuhiro Okazawa 13 November 2018 i Thesis Summary The Scientific Rationality of Early Statistics, 1833–1877 Yasuhiro Okazawa Summary This thesis examines the activities of the Statistical Society of London (SSL) and its contribution to early statistics—conceived as the science of humans in society—in Britain. The SSL as a collective entity played a crucial role in the formation of early statistics, as statisticians envisaged early statistics as a collaborative scientific project and prompted large-scale observation, which required cooperation among numerous statistical observers. -
School of Social Sciences Economics Division University of Southampton Southampton SO17 1BJ, UK
School of Social Sciences Economics Division University of Southampton Southampton SO17 1BJ, UK Discussion Papers in Economics and Econometrics Professor A L Bowley’s Theory of the Representative Method John Aldrich No. 0801 This paper is available on our website http://www.socsci.soton.ac.uk/economics/Research/Discussion_Papers ISSN 0966-4246 Key names: Arthur L. Bowley, F. Y. Edgeworth, , R. A. Fisher, Adolph Jensen, J. M. Keynes, Jerzy Neyman, Karl Pearson, G. U. Yule. Keywords: History of Statistics, Sampling theory, Bayesian inference. Professor A. L. Bowley’s Theory of the Representative Method * John Aldrich Economics Division School of Social Sciences University of Southampton Southampton SO17 1BJ UK e-mail: [email protected] Abstract Arthur. L. Bowley (1869-1957) first advocated the use of surveys–the “representative method”–in 1906 and started to conduct surveys of economic and social conditions in 1912. Bowley’s 1926 memorandum for the International Statistical Institute on the “Measurement of the precision attained in sampling” was the first large-scale theoretical treatment of sample surveys as he conducted them. This paper examines Bowley’s arguments in the context of the statistical inference theory of the time. The great influence on Bowley’s conception of statistical inference was F. Y. Edgeworth but by 1926 R. A. Fisher was on the scene and was attacking Bayesian methods and promoting a replacement of his own. Bowley defended his Bayesian method against Fisher and against Jerzy Neyman when the latter put forward his concept of a confidence interval and applied it to the representative method. * Based on a talk given at the Sample Surveys and Bayesian Statistics Conference, Southampton, August 2008. -
The Contrasting Strategies of Almroth Wright and Bradford Hill to Capture the Nomenclature of Controlled Trials
6 Whose Words are they Anyway? The Contrasting Strategies of Almroth Wright and Bradford Hill to Capture the Nomenclature of Controlled Trials When Almroth Wright (1861–1947) began to endure the experience common to many new fathers, of sleepless nights caused by his crying infant, he characteristically applied his physiological knowledge to the problem in a deductive fashion. Reasoning that the child’s distress was the result of milk clotting in its stomach, he added citric acid to the baby’s bottle to prevent the formation of clots. The intervention appeared to succeed; Wright published his conclusions,1 and citrated milk was eventually advocated by many paediatricians in the management of crying babies.2 By contrast, Austin Bradford Hill (1897–1991) approached his wife’s insomnia in an empirical, inductive manner. He proposed persuading his wife to take hot milk before retiring, on randomly determined nights, and recording her subsequent sleeping patterns. Fortunately for domestic harmony, he described this experiment merely as an example – actually to perform it would, he considered, be ‘exceedingly rash’.3 These anecdotes serve to illustrate the very different approaches to therapeutic experiment maintained by the two men. Hill has widely been credited as the main progenitor of the modern randomised controlled trial (RCT).4 He was principally responsible for the design of the first two published British RCTs, to assess the efficacy of streptomycin in tuberculosis5 and the effectiveness of whooping cough vaccine6 and, in particular, was responsible for the introduction of randomisation into their design.7 Almroth Wright remained, throughout his life, an implacable opponent of this ‘statistical method’, preferring what he perceived as the greater certainty of a ‘crucial experiment’ performed in the laboratory. -
Vital and Health Statistics, Series 4, No. 29
Vital and Health Statistics Reconsidering Age Adjustment Procedures: Workshop Proceedings Series 4: Documents and Committee Reports No. 29 This report contains papers presented at the Workshop on Age-Adjustment, March 7, 1991. Presentations are made by representatives of selected Federal, State, and international institutions dealing with issues in the use of the 1940 U.S. population as a standard for the age-adjustment of official statistics. Manning Feinleib, M.D., Dr.P.H., and Alvan O. Zarate, Ph.D., Editors U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES Public Health Service Centers for Disease Control National Center for Health Statistics Hyattsville, Maryland October 1992 DHHS Publication No. (PHS) 93-1466 Copyright Information All material appearing in this report is in the public domain and may be reproduced or copied without permission; citation as to source, however, is appreciated. Suggested Citation Feinleib M, Zarate AO, eds. Reconsidering age adjustment procedures: Workshop proceedings. National Center for Health Statistics. Vital Health Stat 4(29). 1992. Library of Congress Cataloging-in-Publication Data Reconsidering age-adjustment procedures : workshop proceedings. p. cm.—(Vital and health statistics. Series 4, Documents and committee reports ; no. 29) (DHHS publication ; no. (PHS) 92-1466) ISBN 0-8406-0464-5 1. Epidemiology—United States—Statistical methods—Congresses. 2. Epidemiology—United States—Mathematical models—Congresses. 3. Age distribution (Demography)—United States—Congresses. I. National Center for Health Statistics (U.S.) II. Series. III. Series: DHHS publication ; no. (PHS) 92-1466. RA652.2.M3R43 1992 614.4’273—dc20 92-25492 CIP National Center for Health Statistics Manning Feinleib, M.D., Dr.P.H., Director Jack R. -
John Graunt, James Lind, William Farr, and John Snow
© Smartboy10/DigitalVision Vectors/Getty Images CHAPTER 1 The Approach and Evolution of Epidemiology LEARNING OBJECTIVES By the end of this chapter the reader will be able to: ■ Define and discuss the goals of public health. ■ Distinguish between basic, clinical, and public health research. ■ Define epidemiology and explain its objectives. ■ Discuss the key components of epidemiology (population and frequency, distribution, determinants, and control of disease). ■ Discuss important figures in the history of epidemiology, including John Graunt, James Lind, William Farr, and John Snow. ■ Discuss important modern studies, including the Streptomycin Tuberculosis Trial, Doll and Hill’s studies on smoking and lung cancer, and the Framingham Study. ■ Discuss the current activities and challenges of modern epidemiologists. ▸ Introduction Most people do not know what epidemiology is or how it contributes to the health of our society. This fact is somewhat paradoxical given that epidemi- ology pervades our lives. Consider, for example, the following statements involving epidemiological research that have made headline news: ■ Ten years of hormone drugs benefits some women with breast cancer. ■ Cellular telephone users who talk or text on the phone while driving cause one in four car accidents. ■ Omega-3 pills, a popular alternative medicine, may not help with depression. ■ Fire retardants in consumer products may pose health risks. ■ Brazil reacts to an epidemic of Zika virus infections. 1 2 Chapter 1 The Approach and Evolution of Epidemiology The breadth and importance of these topics indicate that epidemiol- ogy directly affects the daily lives of most people. It affects the way that individuals make personal decisions about their lives and the way that the government, public health agencies, and medical organizations make policy decisions that affect how we live. -
Laura Vaughan
Mapping From a rare map of yellow fever in eighteenth-century New York, to Charles Booth’s famous maps of poverty in nineteenth-century London, an Italian racial Laura Vaughan zoning map of early twentieth-century Asmara, to a map of wealth disparities in the banlieues of twenty-first-century Paris, Mapping Society traces the evolution of social cartography over the past two centuries. In this richly illustrated book, Laura Vaughan examines maps of ethnic or religious difference, poverty, and health Mapping inequalities, demonstrating how they not only serve as historical records of social enquiry, but also constitute inscriptions of social patterns that have been etched deeply on the surface of cities. Society The book covers themes such as the use of visual rhetoric to change public Society opinion, the evolution of sociology as an academic practice, changing attitudes to The Spatial Dimensions physical disorder, and the complexity of segregation as an urban phenomenon. While the focus is on historical maps, the narrative carries the discussion of the of Social Cartography spatial dimensions of social cartography forward to the present day, showing how disciplines such as public health, crime science, and urban planning, chart spatial data in their current practice. Containing examples of space syntax analysis alongside full-colour maps and photographs, this volume will appeal to all those interested in the long-term forces that shape how people live in cities. Laura Vaughan is Professor of Urban Form and Society at the Bartlett School of Architecture, UCL. In addition to her research into social cartography, she has Vaughan Laura written on many other critical aspects of urbanism today, including her previous book for UCL Press, Suburban Urbanities: Suburbs and the Life of the High Street. -
Major GREENWOOD (1880 – 1949)
Major GREENWOOD (1880 – 1949) Publications Three previous publications have included lists of the books, reports, and papers written by, or with contributions by, Major Greenwood; none is complete. With the advantage of electronic searches we have therefore attempted to find all his published works and checked them back to source. Since both father (1854 - 1917) and son (1880 - 1949) had identical names, and both were medically qualified with careers that overlapped, it is sometimes difficult to distinguish the publications of one from those of the other except by their appendages (snr. or jun.), their qualifications (the former also had a degree in law), their locations, their dates, or the subjects they addressed. We have listed the books, reports, and papers separately, and among the last included letters, reviews, and obituaries. Excluding the letters would deprive interested scientists of the opportunity of appreciating Greenwood’s great knowledge of the classics, of history, and of medical science, as well as his scathing demolition of imprecision and poor numerical argument. The two publications in red we have been unable to verify against a source. Books Greenwood M Physiology of the Special Senses (vii+239 pages) London: Edward Arnold, 1910. Collis EL, Greenwood M The Health of the Industrial Worker (xix+450pages) London: J & A Churchill, 1921. Greenwood M Epidemiology, Historical and Experimental: the Herter Lectures for 1931 (x+80 pages) Baltimore: Johns Hopkins Press, and London: Oxford University Press, 1932. Greenwood M Epidemics and Crowd-Diseases: an Introduction to the Study of Epidemiology (409 pages) London: Williams and Norgate, 1933 (reprinted 1935). Greenwood M The Medical Dictator and Other Biographical Studies (213 pages) London: Williams and Norgate, 1936; London: Keynes Press, 1986; revised, Keynes Press, 1987.