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.
168
questions
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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 ...
1
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0answers
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 ...
0
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1answer
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 ...
1
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1answer
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 ...
0
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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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0answers
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 ...
0
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0answers
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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0answers
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 ...
4
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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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0answers
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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0answers
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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0answers
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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0answers
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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0answers
36 views
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 ...
0
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0answers
21 views
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 ...
1
vote
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 ...
2
votes
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:
...
0
votes
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 ...
1
vote
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 ...
0
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0answers
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 ...
0
votes
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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0answers
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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0answers
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 ...
1
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0answers
20 views
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....
1
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1answer
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 ...
0
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0answers
13 views
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 ...
0
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2answers
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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0answers
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 ...
3
votes
0answers
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 ...
1
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0answers
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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0answers
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 ...
2
votes
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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0answers
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 ...
1
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0answers
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 ...
5
votes
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 ...
3
votes
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 ...
0
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0answers
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-...
1
vote
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 ...
1
vote
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?
...
0
votes
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)?
0
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0answers
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 ...
0
votes
0answers
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 ...
3
votes
0answers
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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0answers
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?
1
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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 ...
1
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0answers
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) =...
0
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0answers
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 ...
4
votes
1answer
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 ...
0
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0answers
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:
...
3
votes
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: ...
