05477nam 2200673Ia 450 991014639880332120230721021300.01-282-12322-X97866121232210-470-74053-10-470-74054-X(CKB)1000000000748754(EBL)437418(OCoLC)427565663(SSID)ssj0000239023(PQKBManifestationID)11175361(PQKBTitleCode)TC0000239023(PQKBWorkID)10238829(PQKB)11709323(MiAaPQ)EBC437418(Au-PeEL)EBL437418(CaPaEBR)ebr10307342(CaONFJC)MIL212322(EXLCZ)99100000000074875420090227d2009 uy 0engur|n|---|||||txtccrRobust methods in biostatistics[electronic resource] /Stephane Heritier ... [et al.]Chichester, West Sussex ;Hoboken J. Wiley20091 online resource (294 p.)Wiley Series in Probability and Statistics ;v.825Description based upon print version of record.0-470-02726-6 Includes bibliographical references and index.Robust Methods in Biostatistics; Contents; Preface; Acknowledgments; 1 Introduction; What is Robust Statistics?; Against What is Robust Statistics Robust?; Are Diagnostic Methods an Alternative to Robust Statistics? .; How do Robust Statistics Compare with Other Statistical Procedures in Practice?; 2 Key Measures and Results; Introduction; Statistical Tools for Measuring Robustness Properties; The Influence Function; The Breakdown Point; Geometrical Interpretation; The Rejection Point; General Approaches for Robust Estimation; The General Class of M-estimators; Properties of M-estimatorsThe Class of S-estimatorsStatistical Tools for Measuring Tests Robustness; Sensitivity of the Two-sample t-test; Local Stability of a Test: the Univariate Case; Global Reliability of a Test: the Breakdown Functions; General Approaches for Robust Testing; Wald Test, Score Test and LRT; Geometrical Interpretation; General -type Classes of Tests; Asymptotic Distributions; Robustness Properties; 3 Linear Regression; Introduction; Estimating the Regression Parameters; The Regression Model; Robustness Properties of the LS and MLE Estimators; Glomerular Filtration Rate (GFR) Data ExampleRobust EstimatorsGFR Data Example (continued); Testing the Regression Parameters; Significance Testing; Diabetes Data Example; Multiple Hypothesis Testing; Diabetes Data Example (continued); Checking and Selecting the Model; Residual Analysis; GFR Data Example (continued); Diabetes Data Example (continued); Coefficient of Determination; Global Criteria for Model Comparison; Diabetes Data Example (continued); Cardiovascular Risk Factors Data Example; 4 Mixed Linear Models; Introduction; The MLM; The MLM Formulation; Skin Resistance Data; Semantic Priming Data; Orthodontic Growth DataClassical Estimation and InferenceMarginal and REML Estimation; Classical Inference; Lack of Robustness of Classical Procedures; Robust Estimation; Bounded Influence Estimators; S-estimators; MM-estimators; Choosing the Tuning Constants; Skin Resistance Data (continued); Robust Inference; Testing Contrasts; Multiple Hypothesis Testing of the Main Effects; Skin Resistance Data Example (continued); Semantic Priming Data Example (continued); Testing the Variance Components; Checking the Model; Detecting Outlying and Influential Observations; Prediction and Residual Analysis; Further ExamplesMetallic Oxide DataOrthodontic Growth Data (continued); Discussion and Extensions; 5 Generalized Linear Models; Introduction; The GLM; Model Building; Classical Estimation and Inference for GLM; Hospital Costs Data Example; Residual Analysis; A Class of M-estimators for GLMs; Choice of ψ and w(x); Fisher Consistency Correction; Nuisance Parameters Estimation; IF and Asymptotic Properties; Hospital Costs Example (continued); Robust Inference; Significance Testing and CIs; General Parametric Hypothesis Testing and Variable Selection; Hospital Costs Data Example (continued)Breastfeeding Data ExampleRobust statistics is an extension of classical statistics that specifically takes into account the concept that the underlying models used to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable when the data do not exactly match the postulated models as it is the case for example with outliers. Robust Methods in Biostatistics proposes robust alternatives to common methods used in statistics in general and in biostatistics in particular and illustrates their use on many biomedical datasets. The methods introduced include robustWiley Series in Probability and StatisticsBiometryStatistical methodsBiomathematicsBiometryStatistical methods.Biomathematics.570.1/5195570.15195Heritier Stephane432026MiAaPQMiAaPQMiAaPQBOOK9910146398803321Robust methods in biostatistics2172320UNINA