Questions tagged [robust-standard-error]

Questions related to any kind of robust standard error estimation, including but not limited to clusters-robust, heteroscedasticity/autocorrelation-robust, and related standard errors.

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18 views

Heteroscedasticity-consistent standard errors: Distribution of p-values

When dealing with heteroscedastic data, OLS standard errors are biased and cannot be relied upon. Consider $x_t \sim U(0,2)$, $z_t \sim U(0,2)$, $u \sim N(0, \sqrt{x})$ and $y_t = x_t+u_t$. Now fit ...
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19 views

Correcting for Heteroscedasticity in multiple imputed datasets

I have a question regarding the homogeneity of variance in three regression models of diffrent datasets belonging to the same multiple imputed data. As I used multiple imputation I have to check ...
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20 views

What is the effect of robust estimators of covariance variance (Newey-West) on the VAR model?

What will change in VAR model if I will introduce robust estimators of covariance variance (Newey-West)? Will only the interpretations change and the properties of the model remain the same? Or maybe ...
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61 views

"Fixed effects" Cox proportional hazards model for interval censored data with strata in R

I have a large data set where some observation-periods are right censored (no event observed), others are interval censored (event observed but timing is uncertain), and some events fall into the ...
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2answers
38 views

Estimating robust variance without cluster id in survival model

I built a survival model with coxph. I have a large dataset (1 000 000 instances) and the global model is not proportional. It cannot be improved by introducing time-dependent coefficients or ...
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17 views

VAR model and robust estimators of covariance matrix

I have a VAR(2) model which has autocorrelations (since lag = 8 mostly), even when number of lags for this model are bigger. I got and advice that robust estimators of covariance matrix will help with ...
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38 views

Clustering standard errors for difference in difference

I am running a difference in difference to examine the effect of a merger on petrol prices. I am looking to see whether the prices of company A have increased due to a merger with company B. Local ...
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15 views

Test statistic for regression analysis with robust standard errors

I am looking for the test statistic for a regression analysis (using lm in R) with robust standard errors. As far as I understood the F-statistic from the original model is invalid but I was wondering ...
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1answer
77 views

Robust Variance Estimation in Bayesian Meta-analysis

BACKGROUND I am conducting a meta-analysis using the brms in R with structure akin to the following (leaving out priors, etc. ...
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21 views

comparison of two groups to confirm congruence

I am trying to quantify how well my machine (algorithm) agrees with a panel of human professionals. there is a chance that i am over complicating the situation but ill try and explain simply. 5 ...
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25 views

Robust sandwich standard errors for weighted ordinal logistic regression

Does anyone know if there's an implementation of ordinal logistic regression that takes weights and produces robust standard errors? This would be for IPW (otherwise I will fall back on bootstrapping!)...
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21 views

Robust standard errors (White) under homoscedasticity

Robust standard errors (White standard errors) are given by: $$\hat{V}(b)=(\sum_{i=1}^N x_ix_i')^{-1}(\sum_{i=1}^N e_i^2x_ix_i')(\sum_{i=1}^N x_ix_i')^{-1}$$ This helps us to estimate a asymptotic ...
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63 views

Estimate HAC Covariance Matrix from data by hand - Newey West

Given $T$ realizations for $N$ random variables, $X\in\mathbb{R}^{N\times T}$, I want to estimate the covariance matrix of the data, $\Omega\in\mathbb{R}^{N\times N}$. The sample covariance would be $$...
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Clarifications on when heteroscedasticity-robust (Huber-White's) standard errors are useful and when they're not

Short version Considering the controversy regarding this practice and having learn that heteroscedasticity should be addressed differently, I wondered: In which cases should one consider computing ...
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How to derive NW standard errors for impulse responses from lpirfs package in R or calculate them?

In my thesis, I have to derive impulse responses with IV using 2sls. I use the package in R "lpirfs" and specifically the lp_lin_iv function. My results have F stat and P-value. But I want ...
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1answer
59 views

Is it useful to implement clustered SE in the probit-type models?

For my research, I am implementing a two-stage Heckman procedure. I am working with panel data, so I was wondering if it is common and actually needed to use clustered standard errors for the first ...
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1answer
227 views

How to add robust error variances in glm Poisson model in R? [closed]

I am running two parallel analyses for log poisson regression in R and State. In Stata, there is an option of specifying "robust" within the code, but within the R code: ...
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1answer
49 views

Heterogeneity in residuals

I am very new in here, but I will try my best to create a good question. First of all I am doing some regression on Fama and French 3 factor model and an asset. Thus I am doing a OLS regression, using ...
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2answers
111 views

Correcting (or bootstrapping) the standard errrors for a two stage glm

Cross posted on StackOverflow I want to somehow correct the standard errors of my two stage residual inclusion, where in contrast to the 2SLS, the residuals are included in addition to the ...
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178 views

How do I interpret the results from xtprobit random effects model with robust standard errors in stata?

My probit model has panel data. The dependent variable is a binary outcome that survives = 1 and not survives = 0. I am estimating South Africa's export trade relationships that are import-product ...
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1answer
275 views

Newey-West (1987) t-stats

I have a time-series which is autocorrelated by construction. I have calculated the sample mean of this time-series, and would like to calculate the t-statistic corresponding to the hypothesis that ...
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37 views

Which standard errors should I use in the quaids command in stata?

I am estimating an Almost Ideal Demand System (AIDS) for different meat types using the stata command quaids to calculate price and income elasticities. I have household consumption data over several ...
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26 views

RLM Residuals in Statsmodel Python

I am trying to generate response type residual (y^-y)for RLM using statsmodel: model=smf.rllm('y~x', data=x) results=model.fit() resid=results.resid I have ...
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Heteroscedasticity-consistent standard error is not the same as OLS standard error

Problem I perform the following regression $$ y_i = a + b x_i +\epsilon, \quad \quad i = 1, ..., 21$$ I managed to estimate $\hat a = −0.59$ and $\hat b = 0.069$ with standard error $s.e.(\hat b) = 0....
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29 views

Are there formal measures for classifier or regression robustness?

Are there performance measures that produce a numerical value of the robustness of a classifier or regression. By robustness I mean graceful degradation in performance to unexpected input (similar to ...
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Are Poisson regression with robust SEs and Negative Binomial regression NB1 acceptable when the outcome is the sum of dependent Poisson distributions?

The sum of two variables $X_1$ and $X_2$ with Poisson distribution that are not independent has a Hermite distribution. It seems to me, however, that such distribution is not very popular (I only ...
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238 views

Cox models in R: cluster, strata, robust, and frailty ... modeling grouped/clustered survival data

Consider a situation where we have individual patient survival data from a series of clinical trials of patients treated in a similar way. We might have a dataset that looks like this, with n total ...
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15 views

Multi-level model with crossed random effects, robust standard erorrs yield different results

I'm having trouble setting up a multi-level model with crossed random effects (I just started getting into the topic). My data: Observations (n = 122) are an appearance of a speaker (n = 81) at an ...
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116 views

Correcting for robust/clustered standard errors within the lm function or replacing the results

Cross posted on Stackoverflow with a bounty of 200. EDIT: I think I have to clarify this question a little bit more. So what I am looking for, is a function in which I can provide both the vcov matrix ...
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44 views

Robust standard errors under overlapping observations: confusing simulation results from alternative methods

I have a time series of $h$-step-ahead forecasts $\hat{y}_{t+h|t}$ for $t=1,\dots,T-h$ with $h>1$. I also have the corresponding realized values of their targets $y_{t+h}$ and the corresponding ...
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18 views

Standard error for panel data models and heteroscedastic robust SE

There is something I do not understand on a deeper level on standard errors for panel data models. I know the reason for not using usual heteroscedastic-robust standard-errors is because of auto ...
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1answer
94 views

Heteroskedasticity-Robust Standard Errors in Median Regressions

Does anyone know how to compute heteroskedasticity-robust standard errors in median regressions in R? Assume the following example: ...
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53 views

How to manually inflate standard errors to approximate clustered SEs

I'm reading a handout on clustering here It's not clear to me how to compute $\rho_x$ or $\rho_\epsilon$. What is meant by within-cluster correlation of the regression, or within-cluster error ...
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64 views

How to decide between different robust standard errors?

Specifying my model I ran into some very mild heteroscedasticity problems. Given its superior small-sample properties (my dataset contains 79 observations) I used the HC3 specification of the White ...
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2answers
187 views

Getting understand HAC estimators

Can you help me please with understanding HAC estimator ? I've searched whole internet about it and I didn't find any page which explains clearly algorithm of HAC. I would also see some mathematical ...
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1answer
203 views

How do we obtain p values from a robust mixed regression model in R?

I have yet to find an answer to this problem, so here goes. I am fitting a robust mixed regression model using the robustlmm package on R. Unlike the lme4 package, from which we can obtain p values ...
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32 views

In a multilinear regression, does the usage of White standard errors always correct for heteroscedasticity?

I've calculated a multilinear regression. When testing the assumptions of linear regression, I've come to understand that my model violates the assumption of homoscedasticity (as shown with a Breusch-...
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1answer
643 views

Mixed effects negative binomial with robust standard errors (Huber-white) in R

I would like to fit a random effects model in R using the negative binomial distribution and reporting robust standard errors. I was going to try using the sandwich package to compute the robust ...
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1answer
179 views

Robust SE clustered GLM Gamma Log Link to match GEE Robust SE

How do I get the robust standard errors/sandwich variance estimators for GLM using a Gamma family with a log-link to match the robust standard errors from the GEE output? ...
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1answer
111 views

Test for weak instruments in Stata when using VCE robust [closed]

does anyone know how I can test for weak instruments (one instrument, just identified model) after 2SLS regression in Stata when using robust standard errors (VCE robust)?
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40 views

Sandwich estimators, robust standard errors

I'm using R for modeling linear regression for prediction. Residuals do not met regression assumptions of homoscedasticity, therefore using library(lmtest) and library("sandwich") I've ...
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158 views

How to use HAC errors in VAR model

I would like to use the Newey-West method for the standard errors in a VAR(p)-model (I use statsmodels.tsa.vector_ar). The VAR(p)-model assumes that the residuals ...
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173 views

Why do heteroscedasticity-robust standard errors in logistic regression?

I am following a course on R. At the moment, we are working with logistic regression. The basic form we are taught is this one: ...
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13 views

In regression modeling, are there any caveats to always using robust standard errors?

Aside from efficiency issues, is there anything else to this?
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1answer
115 views

Power analysis for cluster-robust regression

I am planning to run a regression for the model of the form: $y = \beta_0 + \beta_1x_1 + \beta_2x_2 + \beta_3x_1x_2 + \epsilon$ To determine the necessary sample size, I would usually use R's ...
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32 views

Why different regression result with real and excess return as the dependent variable?

I want to test how granted patent, R&D & their ratio predicts real & excess market return. I am doing 2 robust linear regressions: \begin{align} \text{Real Return} \left( t + 1 \right) =...
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96 views

Does the sigma-clipped variance/standard-deviation count as a robust estimator of scale?

Robust estimators of scale, such as the median absolute deviation (MAD) and so on, are less affected by outliers than something like the basic standard deviation/variance. Firstly, is there a specific ...
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221 views

Robust Variance in Stata and R?

There are already a lot of good questions on this topic (e.g., here). But they address complexities that I am not interested in. I have some simple data. I am using basic GLM and OLS, with robust ...
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94 views

My simple regression is homoscedastic - should I use robust standard errors or both?

I've been asked to estimate the following simple regression with the 'appropriate' standard errors at 5% sig level and report the results in a table: ...
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1answer
264 views

Address unequal variance between groups before applying contrasts for a linear model? (r)

My Goal: I have an ordinal factor variable (5 levels) to which I would like to apply contrasts to test for a linear trend. However, the factor groups have heterogeneity of variance. What I've done: ...