LEADER 06076nam 22011293u 450 001 9910130878503321 005 20230725052925.0 010 $a1-283-40542-3 010 $a9786613405425 010 $a1-119-99268-0 010 $a1-119-99267-2 035 $a(CKB)3460000000000088 035 $a(EBL)699338 035 $a(OCoLC)711780380 035 $a(SSID)ssj0000550610 035 $a(PQKBManifestationID)11355726 035 $a(PQKBTitleCode)TC0000550610 035 $a(PQKBWorkID)10509691 035 $a(PQKB)10272546 035 $a(MiAaPQ)EBC699338 035 $a(MiAaPQ)EBC4957130 035 $a(Au-PeEL)EBL4957130 035 $a(CaONFJC)MIL340542 035 $a(EXLCZ)993460000000000088 100 $a20130418d2011|||| u|| | 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aUnderstanding Biostatistics$b[electronic resource] 205 $a1st ed. 210 $aChicester $cWiley$d2011 215 $a1 online resource (392 p.) 225 1 $aStatistics in Practice 300 $aDescription based upon print version of record. 311 $a0-470-66636-6 327 $aUnderstanding Biostatistics; Contents; Preface; 1 Statistics and medical science; 1.1 Introduction; 1.2 On the nature of science; 1.3 How the scientific method uses statistics; 1.4 Finding an outcome variable to assess your hypothesis; 1.5 How we draw medical conclusions from statistical results; 1.6 A few words about probabilities; 1.7 The need for honesty: the multiplicity issue; 1.8 Prespecification and p-value history; 1.9 Adaptive designs: controlling the risks in an experiment; 1.10 The elusive concept of probability; 1.11 Comments and further reading; References 327 $a2 Observational studies and the need for clinical trials2.1 Introduction; 2.2 Investigations of medical interventions and risk factors; 2.3 Observational studies and confounders; 2.4 The experimental study; 2.5 Population risks and individual risks; 2.6 Confounders, Simpson's paradox and stratification; 2.7 On incidence and prevalence in epidemiology; 2.8 Comments and further reading; References; 3 Study design and the bias issue; 3.1 Introduction; 3.2 What bias is all about; 3.3 The need for a representative sample: on selection bias; 3.4 Group comparability and randomization 327 $a3.5 Information bias in a cohort study3.6 The study, or placebo, effect; 3.7 The curse of missing values; 3.8 Approaches to data analysis: avoiding self-inflicted bias; 3.9 On meta-analysis and publication bias; 3.10 Comments and further reading; References; 4 The anatomy of a statistical test; 4.1 Introduction; 4.2 Statistical tests, medical diagnosis and Roman law; 4.3 The risks with medical diagnosis; 4.3.1 Medical diagnosis based on a single test; 4.3.2 Bayes' theorem and the use and misuse of screening tests; 4.4 The law: a non-quantitative analogue; 4.5 Risks in statistical testing 327 $a4.5.1 Does tonsillectomy increase the risk of Hodgkin's lymphoma?4.5.2 General discussion about statistical tests; 4.6 Making statements about a binomial parameter; 4.6.1 The frequentist approach; 4.6.2 The Bayesian approach; 4.7 The bell-shaped error distribution; 4.8 Comments and further reading; References; 4.A Appendix: The evolution of the central limit theorem; 5 Learning about parameters, and some notes on planning; 5.1 Introduction; 5.2 Test statistics described by parameters; 5.3 How we describe our knowledge about a parameter from an experiment 327 $a6.3 Describing the sample: descriptive statistics 330 $aUnderstanding Biostatistics looks at the fundamentals of biostatistics, using elementary statistics to explore the nature of statistical tests. This book is intended to complement first-year statistics and biostatistics textbooks. The main focus here is on ideas, rather than on methodological details. Basic concepts are illustrated with representations from history, followed by technical discussions on what different statistical methods really mean. Graphics are used extensively throughout the book in order to introduce mathematical formulae in an accessible way. Key features 410 0$aStatistics in Practice 606 $aBiometry 606 $aBiometry 606 $aBiostatistics 606 $aModels, Statistical 606 $aBiometry 606 $aModels, Theoretical 606 $aStatistics as Topic 606 $aEpidemiologic Methods 606 $aInvestigative Techniques 606 $aHealth Care Evaluation Mechanisms 606 $aPublic Health 606 $aTherapeutics 606 $aQuality of Health Care 606 $aEnvironment and Public Health 606 $aHealth Care Quality, Access, and Evaluation 606 $aHealth Care 606 $aModels, Statistical 606 $aBiostatistics 606 $aBiology$2HILCC 606 $aHealth & Biological Sciences$2HILCC 606 $aBiology - General$2HILCC 615 4$aBiometry. 615 4$aBiometry. 615 4$aBiostatistics. 615 4$aModels, Statistical. 615 0$aBiometry 615 2$aModels, Theoretical 615 2$aStatistics as Topic 615 2$aEpidemiologic Methods 615 2$aInvestigative Techniques 615 2$aHealth Care Evaluation Mechanisms 615 2$aPublic Health 615 2$aTherapeutics 615 2$aQuality of Health Care 615 2$aEnvironment and Public Health 615 2$aHealth Care Quality, Access, and Evaluation 615 2$aHealth Care 615 2$aModels, Statistical 615 2$aBiostatistics 615 7$aBiology 615 7$aHealth & Biological Sciences 615 7$aBiology - General 676 $a570.1/5195 676 $a570.15195 700 $aKa?lle?n$b Anders$0900114 702 $aKčallâen$b Anders 801 0$bAU-PeEL 801 1$bAU-PeEL 801 2$bAU-PeEL 906 $aBOOK 912 $a9910130878503321 996 $aUnderstanding Biostatistics$92010986 997 $aUNINA