# Questions tagged [sandwich]

Sandwich, or sandwich variance estimation, refers to a method of estimating standard errors from estimating equations that is robust to many model based assumptions. The preferred tag is "robust-standard-error"

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### Robust regression inference and Sandwich estimators

Can you give me an example of the use of sandwich estimators in order to perform robust regression inference? I can see the example in ?sandwich, but I don't quite ...
2k views

### Pairwise comparisons for a regression with sandwich estimates (in R)

The question in short I run a regression in R and made a boxplot of the response variable with grouping by one of the predictor variables. On this boxplot I'd like to add some information about the ...
5k views

### Standard Errors with Weighted Least Squares Regression

For OLS, $\hat{\beta} = (X'X)^{-1}X'y$, and $\text{var}(\hat{\beta}) = (X'X)^{-1} X' \sigma^2 I X (X'X)^{-1}$. I can reproduce these "by hand". For WLS, with heteroskedastic errors and weights in ...
560 views

### Difference between Quasi-Poisson and Sandwich Covariance

I understand that both methods can be utilized to obtain correct inference in overdispersed Poisson data. What I don't understand is the difference between them: why the analyst would choose one over ...
914 views

### Robust Residual standard error (in R)

I have a question regarding to the concept of robust standard errors. What I found about that topic is, that one can estimate the robust standard error for regression coefficients to eliminate ...
251 views

### How to implement the sandwich estimator in a semi-parametric situation?

I am trying to implement a sandwich estimator described in Zhang et al. (2012, p. 1012) in very brief terms. The information they give is not enough for me to understand what has been actually done, ...
2k views

### Sandwich Estimator in Maximum Likelihood Estimation of Logit

I am estimating a discrete choice model using mixed logit using Halton Draws. So everything is effectively done with MCMC. The code is written in MATLAB. I am using MATLAB's ...
2k views

### Robust OLS versus ML with sandwich estimator

If you compare the standard errors of the OLS coefficients with the White correction, versus the ML estimates with the variance estimated with the sandwich estimator, which standard errors do you ...
960 views

### How to calculate sandwich standard errors for generalized least squares models?

Dependent data can be modeled using covariance structures like compound symmetry, spherical, AR-1, and other. Using generalized least squares, inference can be made on the regression coefficients ...
1k views

### Clustered (grouped) standard errors MLE in R

I'm doing the following maximum likelihood estimation using mle2 function from bbmle package: ...
115 views

### effect estimate without constant variance (r sandwich vcovHC)

For the sandwich package in R, when using vcovHC(model) where model <- lm(Y~X), what gives the effect estimate regarding the ...
41 views

### How to compute the sandwich variance ML estimator in R

I'm currently estimating a DCC-type model by maximum likelihood. Im using the command solnp and it return an object where I can compute the Hessian H evaluated at ...