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Questions tagged [robust-standard-error]

Use this tag for 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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Calculate HC3 robust vcov matrix when knowing only of Gradient and Hessian matrices of a GLM model

Suppose that a Generalized Linear Model is fitted using Maximum-Likelihood Estimation, but we only have access to two results from it: the gradient matrix $G$ is a $n \times p$ matrix where each row $...
Parlare's user avatar
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1 answer
36 views

Robust Variance Estimation or Cluster Wild Bootstrapping on a multivariate meta-analysis

Cliffnotes Can I use RVE or cluster wild bootstrapping in meta-analytic models that are not meta-regression? Question I am conducting a three-level meta-analysis looking at the effects of a particular ...
Max Moser's user avatar
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0 answers
19 views

Firm Fixed Effects Model dropping Sector Dummies? Potential Solution?

For my thesis, I am using panel data with stock returns and other firm data. I first used an event study to calculate abnormal returns (with event window of 7 days so 7 observations for 500 firms) ...
mek1401's user avatar
3 votes
2 answers
184 views

Distribution of medians of triplicate samples taken from Gaussian distribution

My Monte Carlo simulation seems to show that the standard deviation of the medians of triplicate samples taken from the Gaussian distribution approaches 2/3 of the SD of the original distribution. ...
Maciej Tomczak's user avatar
2 votes
1 answer
51 views

Maximum likelihood estimation with (robust) Huber-White standard errors appropriate for outlier management?

Is maximum likelihood estimation with robust Huber-White standard errors and a scaled test statistic — which is asymptotically equal to the Yuan-Bentler test statistic — appropriate for data with ...
Madamadam's user avatar
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2 votes
1 answer
42 views

Time series regression on mixed frequency overlapping data

I have an hourly univariate time series. I am trying to see if the next hour, day, week etc changes are forecastable from the past changes. The ACF and PACF of the data both look similar and show some ...
dayum's user avatar
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1 vote
0 answers
19 views

Large $N$, small $T$ in SUR: workaround using system GMM

Consider a system of linear equations as in seemingly unrelated regression (SUR). If the number of equations $N$ is large relative to the sample size $T$, the weighting matrix in SUR (i.e. the error ...
Richard Hardy's user avatar
2 votes
1 answer
100 views

Heterogeneity and ICC when using metafor's rma.mv and robust variance estimation

I am conducting a meta-analysis of standardised mean differences with many sources of dependency (multiple outcomes measuring the same construct, multiple control groups, outcomes from dyads (e.g., ...
AndreasV's user avatar
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0 answers
69 views

How to implement Newey-West standard errors in R?

Im trying to implement newey-west standard errors to correct for issues i had with autocorrelation doing a regression with OLS. But these robust errors only make my results less significant. I have ...
user avatar
1 vote
1 answer
44 views

Heteroscedasticity-consistent (robust) standard errors complemented by i) confidence intervals for beta, ii) Tolerance and iii) VIF values in R?

In order to solve heteroscedasticity in my data, I ran a regression with heteroscedasticity-consistent ("robust") standard errors. I would also like to report i) standardized betas together ...
mbp's user avatar
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3 votes
2 answers
132 views

Large increase in joint significance when introducing robust covariance matrix estimator

I have a linear regression model where $Y$ is regressed on five dummies $X_3,X_4,X_5,X_{10},X_{20}$. (In R, I actually regress $Y$ on a factor $X$ that produces the 5 dummies.) My sample size is 24 (...
Richard Hardy's user avatar
1 vote
0 answers
40 views

Robust standard errors leading to false positives [closed]

I have an odd scenario in my data analysis and I'm not sure what is causing it. I have a large set of tuples $(Y_1, X_i) \dots, (Y_N, X_N)$ where $Y_i$ is a random vector from some arbitrary ...
David Wang's user avatar
3 votes
1 answer
79 views

Application of robust Poisson regression

I am applying a Poisson regression with robust standard errors to model a binary response variables. I was wondering what are the assumptions underlying this type of regression? Does robust Poisson ...
zhiheng yi's user avatar
2 votes
1 answer
62 views

Robust to heteroskedasticity and autocorrelation VIF formula

Classical VIF coefficient calculated using aux regression as $VIF_i = \frac{1}{1 - R^2_i}$. But this formula derived from classical linear model assumptions (spherical matrix of errors) under which $...
kissmemiau's user avatar
1 vote
0 answers
223 views

How to compute robust standard errors for a linear mixed effects model with two non-nested random effects?

I asked this question earlier this week but I hadn't really done my research yet or inquired into my error. So my data is heteroscedastic which has necessitated computation of robust standard errors ...
Shannon Cahalan's user avatar
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0 answers
25 views

Aggregating T-statistics and F-statistics across monthly cross-sectional regressions

I am trying to replicate the results in Table V of the paper Individualism and Momentum around the World (2010) by Chui et al. This is attached herewith. Dataset: Dependent variable: Monthly returns ...
dbjax's user avatar
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How does the heteroskedasticity-robust SE equal the conservative estimator of SE for sample average treatment effect?

I have been told that the heteroskedasticity-robust standard error of $\hat{\beta}_1$ from an OLS regression with a binary $X_i$: $Y_i = \beta_0 + \beta_1 X_i + u$ should be the same as the ...
barbaratoth's user avatar
3 votes
1 answer
166 views

How does Huber compute the $\operatorname{var}(s_n)/E[s_n]^2$ and $\operatorname{var}(d_n)/E[d_n]^2$?

(N.B. I am cross posting this question from math stackexchange since after x days I have still not received any responses.) How does Huber in book 'Robust statistical procedures' in chapter 1 compute ...
peter's user avatar
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1 vote
0 answers
59 views

Robust Standard Errors as Remedy for Violation of Assumptions in Multi-Level Model

So I ran a multi-level model using the nlme/lme4 R packages. Testing the assumptions, I found that level 1 as well as level 2 residuals are not normally distributed, also there's heteroscedasticity on ...
Ben's user avatar
  • 23
1 vote
1 answer
90 views

Does PLM package (PGMM function) use Windmeijer-corrected cluster-robust errors? [closed]

I am performing a GMM analysis using the pgmm function in the plm package in R. I read a lot about different errors (nonrobust, ...
Li4991's user avatar
  • 23
2 votes
2 answers
540 views

Help with the normality of the residuals of my regression model

I am doing a regression in R on the effects of EU and UN economic sanctions on GDP. My model looks like this: ...
slicey's user avatar
  • 31
1 vote
0 answers
37 views

Why are FGLS standard errors so low when estimating linear regression on panel data?

I am currently writing my master thesis an the effect of academic publication on anomaly returns. The idea is that in finance literature anomaly - factors/portfolios are proposed. After the factor is ...
CHRISS's user avatar
  • 11
2 votes
1 answer
526 views

How to correct for serial correlation in an ARDL model without increasing lags?

I'm currently looking to run an ARDL model - I'm able to compute results that show cointegration, however there is serial correlation when I run the Durbin-Watson and Breusch-Godfrey tests. To correct ...
woodvalestar's user avatar
1 vote
1 answer
296 views

Robustification in lavaan: Difference between M, MV and MVS?

In lavaan, I am running a two-factor CFA on a questionnaire with 28 items, all of which are scored on a 6-point Likert scale. In total I have ~350 participants who completed the questionnaire. Because ...
LJFlameling's user avatar
5 votes
1 answer
621 views

Robust standard errors for a Poisson regression with/without an offset

The following is a question posted to Stack Overflow, but the answer is more to-do with statistical theory than software. I am reposting it here because this is a more appropriate venue, and because ...
Demetri Pananos's user avatar
0 votes
1 answer
143 views

Confidence interval from coefficient and robust standard errors

After having run the following regression in Stata regress y x1 x2 ... xn [weight=w], robust I given the following table: Is there a way to get the confidence ...
Fernando Chu's user avatar
3 votes
0 answers
100 views

Clustered vs. GMM-based standard errors: which ones to use in asset pricing?

This question was posted on Quantitative Finance Stack Exchange a while ago. While it was received positively there and generated a reasonable amount of views, no answers have been posted. Thus I am ...
Richard Hardy's user avatar
1 vote
0 answers
126 views

How to conduct a power analysis for a linear regression with clustered standard errors?

I would like to conduct a posthoc power analysis for a linear regression model to see the power of my analysis given the effect size I am finding. However, due to the clustering of standard errors, I ...
Chonasi's user avatar
  • 11
2 votes
0 answers
214 views

How can I estimate robust standard errors for robust estimators? R

I am doing a robust regression and I want to estimate robust standard errors for my regression. I do know how to do a robust regression in R and how to estimate a robust standard errors for a ...
Cristina Mura's user avatar
1 vote
0 answers
62 views

Sandwich Package is not Working Properly [closed]

The sandwich package in R is not working properly. All of the following methods are giving the same results: Regular standard error Robust (HC1)Standard One way ...
Nadal's user avatar
  • 11
1 vote
0 answers
25 views

estimating variance when parameters are estimated

I am trying to understand the sandwich variance estimator. Mainly my confusion is why it is OK to use estimated parameters. I think it boils down to this question. If $f(X_i; \theta),i=1,\ldots,n$ are ...
kimla.2's user avatar
  • 21
1 vote
1 answer
458 views

Manually calculate robust standard errors of 2SLS regression

I used the "systemfit" function in R to estimate a 2SLS model as it allows to specify the first and second stage separately which is important for my estimation. I need robust standard ...
JJ1214's user avatar
  • 11
1 vote
0 answers
89 views

When using both Sattertwaite degrees of freedom adjustment AND sandwich estimator of the covariance, how do they interact?

In longitudinal experimental trials, where typically (relatively) small sample number of participants are examined, two solutions are proposed to address two kinds of issues: robust estimator of the ...
Kaloobin's user avatar
1 vote
1 answer
287 views

Understand robust se vs naive se from marginal means survival model [duplicate]

I ran a marginal means survival model that included some time-invariant and time-varying covariates (see this post for relevant information). I am trying to understand why the robust standard errors ...
cliu's user avatar
  • 211
2 votes
0 answers
63 views

Cluster robust standard error

$$\bf{y}=\bf{X\beta}+\bf{\epsilon}$$ In asymptotic setting, assume: (a) linearity (b) $\{y_i,\bf{x}_i\}$ ergodic stationarity (c) weak exogeneity $E(\bf{x}_i\epsilon_i)=0$ (d) Rank condition $E(\bf{x}...
jasmine's user avatar
  • 367
5 votes
2 answers
389 views

Do I need to test for autocorrelation or normality assumption if I am running the regression with standard errors?

I used OLS regression to estimate a relationship between X and Y with a couple of control variables. However, when I tested for heteroskedasticity with Breusch–Pagan/Cook–Weisberg test, my residuals ...
Laiy's user avatar
  • 245
8 votes
3 answers
2k views

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 ...
garej's user avatar
  • 359
1 vote
1 answer
98 views

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 ...
madina_b's user avatar
1 vote
2 answers
737 views

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 ...
Jenna Clark's user avatar
1 vote
0 answers
92 views

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 ...
DLTS's user avatar
  • 63
1 vote
1 answer
3k views

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: ...
João Areias's user avatar
1 vote
0 answers
70 views

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 ...
Blitzkordk's user avatar
1 vote
1 answer
121 views

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 ...
Brian M.'s user avatar
1 vote
1 answer
241 views

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 ...
giac's user avatar
  • 911
1 vote
0 answers
676 views

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 ...
jean10's user avatar
  • 11
0 votes
0 answers
32 views

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 ...
wrangjangler's user avatar
2 votes
0 answers
231 views

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?
Mia's user avatar
  • 21
2 votes
1 answer
533 views

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 ...
bash1000's user avatar
  • 121
1 vote
1 answer
3k views

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 ...
Andressa TB's user avatar
5 votes
0 answers
1k views

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 ...
Anthony's user avatar
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