Measurement Error in Nonlinear Models: A Modern Perspective, Second EditionCRC Press, 21 juin 2006 - 488 pages 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 ex |
Table des matières
INTRODUCTION | 1 |
IMPORTANT CONCEPTS | 25 |
LINEAR REGRESSION AND ATTENUATION | 41 |
REGRESSION CALIBRATION | 65 |
SIMULATION EXTRAPOLATION | 97 |
INSTRUMENTAL VARIABLES | 129 |
SCORE FUNCTION METHODS | 151 |
LIKELIHOOD AND QUASILIKELIHOOD | 181 |
NONPARAMETRIC ESTIMATION | 279 |
SEMIPARAMETRIC REGRESSION | 303 |
SURVIVAL DATA | 319 |
RESPONSE VARIABLE ERROR | 339 |
BACKGROUND MATERIAL | 359 |
TECHNICAL DETAILS | 385 |
413 | |
439 | |
BAYESIAN METHODS | 205 |
HYPOTHESIS TESTING | 243 |
LONGITUDINAL DATA AND MIXED MODELS | 259 |
Author Index | 441 |
447 | |
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Expressions et termes fréquents
algorithm analysis assumed assumptions asymptotic attenuation Bayesian Berkson model bias biased bootstrap Carroll Chapter classical error classical measurement error coefficient components compute consistent estimators corrected score covariance matrix covariate measurement data set deconvolution defined described discussed effects of measurement eGFR estimating equations example extrapolant Figure Framingham Gibbs sampler given homoscedastic independent instrumental variable intake iteration least squares likelihood function linear model logistic regression M-estimator maximum likelihood mean zero measured with error measurement error model measurement error variance methods misclassification Monte Carlo multiplicative naive estimator naive test nonlinear nonlinear regression nonparametric regression normally distributed observed data parameters plot posterior predictor problem quadratic random variables regression model response Ruppert sample score function Section segmented regression SIMEX SIMEX estimator simulation spline standard errors Statistical Stefanski surement error surrogate tion true unbiased validation data values variance estimator variance function vector Wang WinBUGS