Celebrating twenty years of transition from socialism to capitalism, this book is designed to be the core textbook for undergraduate courses in transition economics and comparative economic systems. Given the passage of time, Transition Economics: Two Decades On reviews and accounts for the outcomes in the so-called transition economies and, from an academic perspective, takes the reader through developments and issues in the twenty years of transition from plan to market.
Treating its subject matter thematically, the book incorporates much of the transition economics 606 $aEconomic history$vCase studies 606 $aMixed economy$vCase studies 606 $aStructural adjustment (Economic policy)$vCase studies 606 $aSocial change$vCase studies 615 0$aEconomic history 615 0$aMixed economy 615 0$aStructural adjustment (Economic policy) 615 0$aSocial change 676 $a330.12/6 700 $aTurley$b Gerard.$0887622 701 $aLuke$b Peter J$01588466 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910800064503321 996 $aTransition economics$93878250 997 $aUNINA LEADER 05632nam 22006734a 450 001 9910830922703321 005 20230617011807.0 010 $a1-280-26930-8 010 $a9786610269303 010 $a0-470-09259-9 010 $a0-470-09260-2 035 $a(CKB)111087027142156 035 $a(EBL)164885 035 $a(OCoLC)54357012 035 $a(SSID)ssj0000109295 035 $a(PQKBManifestationID)11138436 035 $a(PQKBTitleCode)TC0000109295 035 $a(PQKBWorkID)10045696 035 $a(PQKB)11616196 035 $a(MiAaPQ)EBC164885 035 $a(EXLCZ)99111087027142156 100 $a20030821d2004 uy 0 101 0 $aeng 181 $ctxt 182 $cc 183 $acr 200 10$aBayesian approaches to clinical trials and health care evaluation$b[electronic resource] /$fDavid J. Spiegelhalter, Keith R. Abrams, Jonathan P. Myles 210 $aChichester ;$aHoboken, NJ $cWiley$dc2004 215 $a1 online resource (408 p.) 225 1 $aStatistics in practice 300 $aDescription based upon print version of record. 311 $a0-471-49975-7 320 $aIncludes bibliographical references (p. 357-380) and index. 327 $aBayesian Approaches to Clinical Trials and Health-Care Evaluation; Contents; Preface; List of examples; 1 Introduction; 1.1 What are Bayesian methods?; 1.2 What do we mean by 'health-care evaluation'?; 1.3 A Bayesian approach to evaluation; 1.4 The aim of this book and the intended audience; 1.5 Structure of the book; 2 Basic Concepts from Traditional Statistical Analysis; 2.1 Probability; 2.1.1 What is probability?; 2.1.2 Odds and log-odds; 2.1.3 Bayes theorem for simple events; 2.2 Random variables, parameters and likelihood; 2.2.1 Random variables and their distributions 327 $a2.2.2 Expectation, variance, covariance and correlation 2.2.3 Parametric distributions and conditional independence; 2.2.4 Likelihoods; 2.3 The normal distribution; 2.4 Normal likelihoods; 2.4.1 Normal approximations for binary data; 2.4.2 Normal likelihoods for survival data; 2.4.3 Normal likelihoods for count responses; 2.4.4 Normal likelihoods for continuous responses; 2.5 Classical inference; 2.6 A catalogue of useful distributions*; 2.6.1 Binomial and Bernoulli; 2.6.2 Poisson; 2.6.3 Beta; 2.6.4 Uniform; 2.6.5 Gamma; 2.6.6 Root-inverse-gamma; 2.6.7 Half-normal; 2.6.8 Log-normal 327 $a2.6.9 Student's 2.6.10 Bivariate normal; 2.7 Key points; Exercises; 3 An Overview of the Bayesian Approach; 3.1 Subjectivity and context; 3.2 Bayes theorem for two hypotheses; 3.3 Comparing simple hypotheses: likelihood ratios and Bayes factors; 3.4 Exchangeability and parametric modelling*; 3.5 Bayes theorem for general quantities; 3.6 Bayesian analysis with binary data; 3.6.1 Binary data with a discrete prior distribution; 3.6.2 Conjugate analysis for binary data; 3.7 Bayesian analysis with normal distributions; 3.8 Point estimation, interval estimation and interval hypotheses 327 $a3.9 The prior distribution 3.10 How to use Bayes theorem to interpret trial results; 3.11 The 'credibility' of significant trial results*; 3.12 Sequential use of Bayes theorem*; 3.13 Predictions; 3.13.1 Predictions in the Bayesian framework; 3.13.2 Predictions for binary data*; 3.13.3 Predictions for normal data; 3.14 Decision-making; 3.15 Design; 3.16 Use of historical data; 3.17 Multiplicity, exchangeability and hierarchical models; 3.18 Dealing with nuisance parameters*; 3.18.1 Alternative methods for eliminating nuisance parameters*; 3.18.2 Profile likelihood in a hierarchical model* 327 $a3.19 Computational issues 3.19.1 Monte Carlo methods; 3.19.2 Markov chain Monte Carlo methods; 3.19.3 WinBUGS; 3.20 Schools of Bayesians; 3.21 A Bayesian checklist; 3.22 Further reading; 3.23 Key points; Exercises; 4 Comparison of Alternative Approaches to Inference; 4.1 A structure for alternative approaches; 4.2 Conventional statistical methods used in health-care evaluation; 4.3 The likelihood principle, sequential analysis and types of error; 4.3.1 The likelihood principle; 4.3.2 Sequential analysis; 4.3.3 Type I and Type II error; 4.4 P-values and Bayes factors* 327 $a4.4.1 Criticism of P-values 330 $aREAD ALL ABOUT IT! David Spiegelhalter has recently joined the ranks of Isaac Newton, Charles Darwin and Stephen Hawking by becoming a fellow of the Royal Society. Originating from the Medical Research Council's biostatistics unit, David has played a leading role in the Bristol heart surgery and Harold Shipman inquiries. Order a copy of this author's comprehensive text TODAY! The Bayesian approach involves synthesising data and judgement in order to reach conclusions about unknown quantities and make predictions. Bayesian methods have become increasingly popular in recent years, notab 410 0$aStatistics in practice. 606 $aBayesian statistical decision theory 606 $aMedicine$xResearch$xStatistical methods 606 $aClinical trials$xStatistical methods 615 0$aBayesian statistical decision theory. 615 0$aMedicine$xResearch$xStatistical methods. 615 0$aClinical trials$xStatistical methods. 676 $a519.5/42/02461 676 $a610.72 700 $aSpiegelhalter$b D. J$065673 701 $aAbrams$b K. R$g(Keith R.)$01691112 701 $aMyles$b Jonathan P$01691113 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830922703321 996 $aBayesian approaches to clinical trials and health care evaluation$94067277 997 $aUNINA