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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Error structure for fixed effects model

Just theoretically, I am wondering about use cases for cluster-robust standard errors and fixed effects models in conjunction. Let's say I have a panel 10 firms over 20 years and I choose to use fixed ...
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Can robust standard errors be less than those from normal OLS?

I'm reading about Robust Standard Error Estimators for Panel Models from the developer of plm R package (Millo, 2017: 21). But my question is not about software. In ...
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how to interpret robustness result

I ran a multivariate meta-analysis to account for dependencies of effect sizes using metafor and then I also applied a robustness check using the ...
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Are "sandwich" robust standard error-correcting estimators also robust to (Missingness) Missing At Random, MNAR? [closed]

From the sandwich package: Huer-White sandwich covariance methods include: heteroscedasticityconsistent (HC) covariances for cross-section data; heteroscedasticity- and autocorrelation-consistent (...
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What is estimated error of the Tukey biweight mean

I have some largely normal data that is infested with outliers. I'm happy with the results I am getting from Tukey biweight mean and would like to estimate the error in that mean. I have small sample ...
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Post hoc test after resolving heterogeneity

Let's say I have a question to be asked: Which groups are significantly different from each other?. So far, I used one way anova method to depict the differences. ...
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Assumption test in latent profile analysis (TidyLPA, R studio)

I'm planning on conducting an LPA of various personality traits and emotion regulation strategies however conducting after some hierarchal linear regressions beforehand I've found that many of the ...
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Does using robust standard errors change effect size?

I ran some linear regressions in R using lm, with an interaction term (cat x cat) as the predictor of interest (and also incorporating a covariate). To calculate the effect sizes of the interaction as ...
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The math behind svyglm() when we have weights and clusters

I want to apply survey::svyglm() to a scenario that we need to get the robust standard error in both weights and clusters. There is an example in survey R package: ...
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HAC estimator in GARCH models

In my time-series class we learned that the HAC estimator is only applicable to correct the standard error (SE) if the underlying series is stationary. Now, GARCH models are unconditionally stationary ...
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Getting confidence interval for prediction from statsmodel Robust Linear model

I'm using statsmodels to fit a statistical model. I have a formula that is fitted like this: ...
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For repeated data, why we don't use just OLS with sandwich SEs but rather GLS or mixed models?

If I have repeated observations and want to summarize the means at each time point, the OLS will give me the true, raw means, while the GLS will give me means dependent on the selected covariance ...
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GLS vs. OLS with sandwich (or GEE with sandwich?) - repeated data (no covariates!) [duplicate]

Let's assume I have a series of repeated observations at time t0..t3. I want to test the difference at each time point vs. t0. When doing a set of independent comparisons "vs. control" (...
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geeglm: Does as.factor() not work with corstr=fixed?

(See "Edits" at the bottom for partial resolution.) I am interested in generating point estimates for each cluster in my data using geeglm.  However, when I use as.factor() over the ...
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What is the difference between robustlmm and clubsandwich in R?

Excuse my ignorance, I am trying to get around a problem with my statistics that involves severe outliers issues, with heteroskeskedacity. My model using linear mixed models, in R, with repeated ...
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Heteroskedasticity in OLS which best: clustered SE or robust SE?

I am trying to estimate the effect of a change in minimum wage regulation with no control group. I computed a propensity score for the probability of being affected by the change in MW before the new ...
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Matching using R -- complex design with repeated controls

I am seeking help on using Matching with R on a particular data structure. I reproduce below the general idea how the data looks like. I have a "pool of control" units that I want to re-used ...
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Robust standard errors for mixed effects models in R

I understand that you cannot fit a glmer(via "lme4") then test using robust SE estimator. Ie ...
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Derivation of Distribution for the Robust F-statistic

This question is motivated by the question here. That question asked about the formula for a robust F-statistic. I am aware of the formula. My question is how to prove the distribution of the test ...
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Which standard errors?

I'm working on a project with panel data and decided to use the fixed effect model, because the hausmann test p-value < 0,05. No I wonder ho do I know, which standard errors should I use? There are ...
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difference between standard error and robust standard error

What is the difference between standard error vs robust standard error? How is the robust standard error calculated in the Generalized Estimating Equation context?
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Is there a method for estimating heteroskedasticity-robust standard errors for a Heckman/heckit model in R?

I am trying to figure out how to estimate a Type II Tobit/Heckman/heckit model in R and extract heteroskedasticity robust standard errors. It would be nice if the standard errors were robust for both ...
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Country fixed effects and clustered robust standard errors for logistic regression

I'm wondering if in the same analysis I can use countries as fixed effect and as a cluster for the robust standard errors. Background: I'm running a multivariate logistic regression with the ...
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HAC standard errors: small-sample correction

The Python package statsmodels provides a use_correction option when computing HAC standard errors for an OLS model, which ...
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Autocorrelation Correction to Covariance

This is a follow-up to my previous question about autocorrelation impact on estimation of statistical quantities. I want to estimate covariance matrix and Pearson's correlation matrix for stationary ...
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How to compute sandwich estimator with QMLE and Poisson regression in R (using glmrob package)

I am trying to applying a sandwich estimator to a Poisson regression with QMLE in R, where I used the glmrob function. The code I am using looks like: ...
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are zero-variance random effects generated by robustlmm, of the sort that generate IsSingluar warnings in lme4, a problem?

I am modeling data I described here. I have stopped treating clusters individually and have since averaged them, so now I have three experimental conditions, Type, Relevance, and Taught. Type has ...
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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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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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"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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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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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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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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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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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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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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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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When are heteroscedasticity-robust (Huber-White's) standard errors useful and when are they not? [closed]

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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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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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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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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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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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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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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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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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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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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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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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 ...