To see accurate pricing, please choose your delivery country.
United States
All Shops

British Wildlife

8 issues per year 84 pages per issue Subscription only

British Wildlife is the leading natural history magazine in the UK, providing essential reading for both enthusiast and professional naturalists and wildlife conservationists. Published eight times a year, British Wildlife bridges the gap between popular writing and scientific literature through a combination of long-form articles, regular columns and reports, book reviews and letters.

Subscriptions from £33 per year

Conservation Land Management

4 issues per year 44 pages per issue Subscription only

Conservation Land Management (CLM) is a quarterly magazine that is widely regarded as essential reading for all who are involved in land management for nature conservation, across the British Isles. CLM includes long-form articles, events listings, publication reviews, new product information and updates, reports of conferences and letters.

Subscriptions from £26 per year
Academic & Professional Books  Reference  Data Analysis & Modelling  Modelling

Measurement Error in Nonlinear Models A Modern Perspective

By: RJ Carroll, David Ruppert, Leonard A Stefanski and Ciprian Crainiceanu
455 pages, Figs
Measurement Error in Nonlinear Models
Click to have a closer look
  • Measurement Error in Nonlinear Models ISBN: 9781584886334 Edition: 2 Hardback Jun 2006 Not in stock: Usually dispatched within 1-2 weeks
Price: £130.00
About this book Contents Customer reviews Related titles

About this book

It's been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and extensively updated to offer the most comprehensive and up-to-date survey of measurement error models currently available.

What's new in the Second Edition?
* Greatly expanded discussion and applications of Bayesian computation via Markov Chain Monte Carlo techniques
* A new chapter on longitudinal data and mixed models
* A thoroughly revised chapter on nonparametric regression and density estimation
* A totally new chapter on semiparametric regression
* Survival analysis expanded into its own separate chapter
* Completely rewritten chapter on score functions
* Many more examples and illustrative graphs
* Unique data sets compiled and made available online

In addition, the authors expanded the background material in Appendix A and integrated the technical material from chapter appendices into a new Appendix B for convenient navigation. Regardless of your field, if you're looking for the most extensive discussion and review of measurement error models, then Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition is your ideal source.


Guide to NotationINTRODUCTIONThe Double/Triple-Whammy of Measurement ErrorClassical Measurement Error A Nutrition ExampleMeasurement Error ExamplesRadiation Epidemiology and Berkson ErrorsClassical Measurement Error Model ExtensionsOther Examples of Measurement Error ModelsChecking The Classical Error ModelLoss of PowerA Brief TourBibliographic NotesIMPORTANT CONCEPTSFunctional and Structural ModelsModels for Measurement ErrorSources of DataIs There an "Exact" Predictor? What is Truth?Differential and Nondifferential ErrorPredictionBibliographic NotesLINEAR REGRESSION AND ATTENUATIONIntroductionBias Caused by Measurement ErrorMultiple and Orthogonal RegressionCorrecting for BiasBias Versus VarianceAttenuation in General ProblemsBibliographic NotesREGRESSION CALIBRATIONOverviewThe Regression Calibration AlgorithmNHANES ExampleEstimating the Calibration Function ParametersMultiplicative Measurement ErrorStandard ErrorsExpanded Regression Calibration ModelsExamples of the ApproximationsTheoretical ExamplesBibliographic Notes and SoftwareSIMULATION EXTRAPOLATIONOverviewSimulation Extrapolation HeuristicsThe SIMEX AlgorithmApplicationsSIMEX in Some Important Special CasesExtensions and Related MethodsBibliographic NotesINSTRUMENTAL VARIABLESOverviewInstrumental Variables in Linear ModelsApproximate Instrumental Variable EstimationAdjusted Score MethodExamplesOther MethodologiesBibliographic NotesSCORE FUNCTION METHODSOverviewLinear and Logistic RegressionConditional Score FunctionsCorrected Score FunctionsComputation and Asymptotic ApproximationsComparison of Conditional and Corrected ScoresBibliographic NotesLIKELIHOOD AND QUASILIKELIHOODIntroductionSteps 2 and 3: Constructing LikelihoodsStep 4: Numerical Computation of LikelihoodsCervical Cancer and HerpesFramingham DataNevada Test Site ReanalysisBronchitis ExampleQuasilikelihood and Variance Function ModelsBibliographic NotesBAYESIAN METHODSOverviewThe Gibbs SamplerMetropolis-Hastings AlgorithmLinear RegressionNonlinear ModelsLogistic RegressionBerkson ErrorsAutomatic implementationCervical Cancer and HerpesFramingham DataOPEN Data: A Variance Components ModelBibliographic NotesHYPOTHESIS TESTINGOverviewThe Regression Calibration ApproximationIllustration: OPEN DataHypotheses about Sub-Vectors of x and zEfficient Score Tests of H0 : x = 0Bibliographic NotesLONGITUDINAL DATA AND MIXED MODELSMixed Models for Longitudinal DataMixed Measurement Error ModelsA Bias Corrected EstimatorSIMEX for GLMMEMsRegression Calibration for GLMMsMaximum Likelihood EstimationJoint ModelingOther Models and ApplicationsExample: The CHOICE StudyBibliographic NotesNONPARAMETRIC ESTIMATIONDeconvolutionNonparametric RegressionBaseline Change ExampleBibliographic NotesSEMIPARAMETRIC REGRESSIONOverviewAddi

Customer Reviews

By: RJ Carroll, David Ruppert, Leonard A Stefanski and Ciprian Crainiceanu
455 pages, Figs
Current promotions
Field Guide SaleNHBS Moth TrapNew and Forthcoming BooksBuyers Guides