[PDF] Top 20 Correcting data for measurement error in generalized linear models
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Correcting data for measurement error in generalized linear models
... As all of the bias-adjusted estimators are modified M-estimators or what might be called pseudo M-estimators, a routine though tedious application of the delta method yields standard lar[r] ... See full document
20
Efficient estimation in a class of generalized linear measurement-error models
... Of the more popular generalized linear models (McCullugh & NeIder, 1983) (MI) excludes only the normal model, for which Bickel & Ritov (1986) have already constructed efficient e[r] ... See full document
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Estimation of Nonparametric Multiple Regression Measurement Error Models with Validation Data
... surrogate data and validation ...local linear regression and Fourier transformation method when both explanatory and surrogate variable are ...regression models with measurement errors, ones ... See full document
12
Estimation in a linear multivariate measurement error model with a change point in the data
... The EIV models with two or more unknown noise parameters, however, are non- identifiable by second order methods. This problem of non-identifiability is well known in the context of the Frisch scheme, see Frisch ... See full document
22
Power of Simulation Extrapolation in Correction of Covariates Measured with Errors
... the measurement of values of variables in order to make valid conclusions for decision ...in correcting the bias of coefficients of a logistic regression model with one covariate measured with ...Square ... See full document
5
Generalized Inference in Linear Regression Models
... in linear regression under both ho- moscedasticity and heteroscedasticity of the error ...and generalized confidence intervals for regression coeffi- cients of linear regression ...regression ... See full document
106
Robustness of zero augmented models over generalized linear models in analysing fertility data in Nigeria
... fertility data at national level and with the use of a particular model is likely to be fraught with hidden errors due to the peculiarities of the number of zeros and level of skewness inherent across regional ... See full document
7
Detection of Outliers and Influential Observations in Linear Ridge Measurement Error Models with Stochastic Linear Restrictions
... The group structure among the objects arises from two main sources, fabric code and location of pottery. Both of these subdivisions are important to the archaeologists. Consequently, according to this group structure, ... See full document
12
Generalized linear mixed models for count data
... Theoretically, the EM algorithm is the most accurate method that we have dis- cussed so far. Unlike the Laplace approximation and Gauss-Hermite quadrature, where we have to worry about the coefficients of the ... See full document
97
Simulation-extrapolation: The measurement error jackknife
... It is shown that the variance estimator is asymptotically valid in simple linear regression measurement error models.. Data from the Framingham Heart Study.[r] ... See full document
35
Using generalized linear models to model compositional response data
... the generalized Wedderburn ...the generalized Wedderburn approach are actually slightly ...the generalized Wed- derburn method are very similar to those achieved using Aitchison’s approach, with the ... See full document
183
Orthogonal Series Estimation of Nonparametric Regression Measurement Error Models with Validation Data
... [11] Yu, S.H. and Wang, D.H. (2014) Empirical Likelihood for First-Order Autoregres- sive Error-in-Variable of Models with Validation Data. Communications in Statis- tics Theory Methods, 43, ... See full document
12
Score tests in generalized linear measurement error models
... The solid line is the density estimate based 01\ all the data, while the dashed line is the estimate for the 37 cases of breast. cancer[r] ... See full document
21
Partially linear models
... partially linear regression smoothing in ...partially linear regression ...partially linear regression techniques to various statistical ...censored data analysis, linear ... See full document
216
Unbiased estimation of a nonlinear function of a normal mena with application to measurement-error models
... Key Words and Phrases: errors-in-variables; functional models; generalized linear model; H-estimation; measurement error; structural IIIOdels; unbiased estimation... ABSTRACT.[r] ... See full document
26
Estimators For Generalized Linear Measurement Error Models With Interaction Terms
... normal linear regression ...the error-prone ...the error-free and error-prone ...to measurement er- ror, and unbiased estimators generally perform better in larger sample ... See full document
115
Instrumental variable estimation in generalized linear measurement error models
... The problem of finding efficient, consistent estimators of parameters for a general regression function in the presence of covariate measurement error has not been solved. The problem wi[r] ... See full document
115
Estimating the Parameters Geographically Weighted Regression (GWR) with Measurement Error
... the measurement errors such as [7] in the logistic regression model of the development of heart ...ment error in the generalized linear model ...the measurement error trace which ... See full document
5
Linear Secret Sharing Schemes from Error Correcting Codes and Universal Hash Functions
... It is well known that there is a natural correspondence between linear codes and LSSS [22,4,10]. Since there is a rich body of literature about codes with efficient encoding and decoding, one might hope that this ... See full document
18
CPMCGLM: an R package for p-value adjustment when looking for an optimal transformation of a single explanatory variable in generalized linear models
... PAQUID is a longitudinal, prospective study of individ- uals aged at least 65 years on December 31, 1987 liv- ing in the community in France. These residents live in two administrative areas in southwestern France. This ... See full document
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