This article discusses estimates of variance for two-stage models. We present the sandwich estimate of variance as an alternative to the Murphy–Topel estimate. The sandwich estimator has a simple formula that is similar to the formula for the Murphy–Topel estimator, and the two estimators are asymptotically equal when the assumed model distributions are true. The advantages of the sandwich estimate of variance are that it may be calculated for the complete parameter vector, and that it requires estimating equations instead of fully specified log likelihoods
Abstract: This note explores variance estimation of a combined ratio estimator from a purely model-b...
In this paper we propose a new variance estimator for OLS as well as for non-linear estimators such ...
summary:The paper deals with the estimation of unknown vector parameter of mean and scalar parameter...
This article discusses estimates of variance for two-stage models. We present the sandwich estimate ...
The sandwich estimator, often known as the robust covariance matrix estimator or the empirical covar...
The sandwich estimator, also known as the robust covariance matrix estimator, has achieved increasin...
The aim of this note is to provide a general framework for the analysis of the robustness properties...
The Two-Sample Two-Stage Least Squares (TS2SLS) data combination estimator is a popular estimator fo...
AbstractThe Two-Sample Two-Stage Least Squares (TS2SLS) data combination estimator is a popular esti...
summary:The paper deals with a linear model with linear variance-covariance structure, where the lin...
summary:The paper deals with a linear model with linear variance-covariance structure, where the lin...
A variety of estimators of the variance of the general regression (GREG) estimator of a mean have be...
summary:The paper deals with a linear model with linear variance-covariance structure, where the lin...
This paper considers the problem of estimating the dispersion parameter in a Gaussian model which is...
In this paper we propose a variance estimator for the OLS estimator as well as for nonlinear estimat...
Abstract: This note explores variance estimation of a combined ratio estimator from a purely model-b...
In this paper we propose a new variance estimator for OLS as well as for non-linear estimators such ...
summary:The paper deals with the estimation of unknown vector parameter of mean and scalar parameter...
This article discusses estimates of variance for two-stage models. We present the sandwich estimate ...
The sandwich estimator, often known as the robust covariance matrix estimator or the empirical covar...
The sandwich estimator, also known as the robust covariance matrix estimator, has achieved increasin...
The aim of this note is to provide a general framework for the analysis of the robustness properties...
The Two-Sample Two-Stage Least Squares (TS2SLS) data combination estimator is a popular estimator fo...
AbstractThe Two-Sample Two-Stage Least Squares (TS2SLS) data combination estimator is a popular esti...
summary:The paper deals with a linear model with linear variance-covariance structure, where the lin...
summary:The paper deals with a linear model with linear variance-covariance structure, where the lin...
A variety of estimators of the variance of the general regression (GREG) estimator of a mean have be...
summary:The paper deals with a linear model with linear variance-covariance structure, where the lin...
This paper considers the problem of estimating the dispersion parameter in a Gaussian model which is...
In this paper we propose a variance estimator for the OLS estimator as well as for nonlinear estimat...
Abstract: This note explores variance estimation of a combined ratio estimator from a purely model-b...
In this paper we propose a new variance estimator for OLS as well as for non-linear estimators such ...
summary:The paper deals with the estimation of unknown vector parameter of mean and scalar parameter...