Questions tagged [clustered-standard-errors]

Clustered standard errors represent the version of the general sandwich variance estimator that correct for (potential) grouping of the observations, e.g., repeated measurements clustered within an individual, or individuals clustered within a hierarchy level (geographical region, educational institution, etc.).

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Estimating proportions & 95% CIs with clustered data from very few clusters

What are the best method(s) to estimate a proportion and its associated 95% confidence interval (ideally with an option for an exact method to avoid values +/- 100 or 0) when the data are clustered, ...
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Clustered (grouped) standard errors MLE in R

I'm doing the following maximum likelihood estimation using mle2 function from bbmle package: ...
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Is clustering a necessity?

this is a cross-post. The original question (i had to move the link to the comments to be able to include results) was posted on Statalist, the 17.2.2016. First the question, because possibly it can ...
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Pooled OLS: how to correct for serial correlation of residuals

I am trying to follow the procedure offered by Beck and Katz 1995 in a way that I also have a TSCS data with $T=100$ (time dimension) and $N=12$ (unit dimension). My data is not balanced, which means ...
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1answer
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Cluster-robust SE in Stata when using a survey design

I'm working with data from a clustered sample where observations have a certain sampling weight (pweight). There are two ways to obtain the correct point estimates: I) using reg yvar xvar [pw = ...
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1answer
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random effects and clustered errors

I am running a panel model using an linear regressor. A Haussman test indicates that the random effects model is better than a fixed effects. I am also clustering the errors on country code. I would ...
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When to use fixed effects vs using cluster SEs?

Suppose you have a single cross-section of data where individuals are located within groups (e.g. students within schools) and you wish to estimate a model of the form ...
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1answer
687 views

Wild Cluster Bootstrap and GLM

I am a Stata user and am trying to determine the most appropriate method for improving statistical inference in GLM (generalized linear models) applications with very few clusters (in one study G=29 ...
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1answer
316 views

CART and Clustered Data?

Just wonder if there is any caveat if one fits regular regression trees to clustered data but ignores the clustered structure of the data. More generally, how bad it would be if we fit regression ...
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401 views

Can you have too many clusters in your standard errors?

I know the problems of there being 'too few' clusters when using clustered standard errors, but are there problems with using 'too many'? For instance, I have 1million observations, and 2500 ...
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Clustering errors in Panel Data at the ID level and testing its necessity

What are the possible problems, regarding the estimation of your standard errors, when you cluster the standard errors at the ID level? And how does one test the necessity of clustered errors? When ...
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What level should I cluster at in my regression?

So I am running a pooled OLS. My dependent variable is house prices, and my main explanatory variables are job creation and distance to job creation, plus a raft of control variables. The housing ...
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802 views

Clustered data in logistic regression analysis

I am doing a logistic regression analysis, for an election setting. My dependent variable is voting for the incumbent candidate (Yes/No) and my independent variable is perceived economy (data from a ...
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Robust Coefficients For Differences in Differences

I have a panel data set which I am looking to analyze for relationships/causality using the OLS differences-in-differences method. The panel data includes multiple observations over time for various ...
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Standard error clustering under treatment assignment in groups of varying size

Basic setup: Unit of observation is the individual. Treatment (binary) is assigned on city level. Every state contains 4 cities, 2 get randomly chosen for treatment, 2 control. There are only few (e....
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Use SUR to measure unobservable effects?

My title is a littel bit ambiguous. I'm working on a project on measure the degree of sorting in housing market,put it simple, sorting refers to people with similar characteristics tend to live in ...
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427 views

cluster standard errors with small group sizes but large number of groups

I have tried looking for cluster standard errors and the only reference that I found are that problems will arise if the group is small but group size is large. However, in the case when group size ...
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Arellano cluster-robust standard errors with households fixed effects: what about the village level?

Consider the following regression line: $y_{i,t}=b_0+b_1X_{t,g}+a_{i}+e_{i,t}$ where $y_{i,t,g}$ is the consumption of household $i=1,..,N$, at time $t=1,...,T$, $X_{t,g}$ is a weather index ...
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Cluster Robust Standard Errors vs GMM

I want to estimate a linear model on a panel data set using fixed effects and my dependent variable has positive serial correlation. I also have to address heteroskedasticity. I have read that two-way ...
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1answer
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Procedure for the cluster-robust Hausman test

The Hausman test cannot be run on robust std. errors we have separately make the FE and RE standard errors robust to serial correlation and heteroskedasticity by clustered standard errors. So, is ...
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Clustering in Instrumental Variables Regression?

I am wondering whether clustering in IV estimation would mean I have a fixed effect for both error terms or just for the structural error. For example, in the model \begin{eqnarray} y = X \beta + \...
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Clustering standard errors for respondents who move during treatment period

I am conducting an impact evaluation, but the question applies generally to any situation where observations move between cluster-units during the course of treatment. I am using robust standard ...
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1answer
191 views

Analysis of clustered data

I have records of $multiple$ visits from many different patients in several different clinics (i.e. visits nested within patients nested within clinic) and plan to perform an analysis that takes into ...
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256 views

Identification of Difference in Weighted Mean and its Standard Error in Clustered Data Using Stata

I already asked this question on the statalist but have not received any comments on this issue yet. So I am going to post it here too. I am concerned with the following problem. Suppose my data ...
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1answer
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Example of multi-way clustering robust standard errors: puzzling results

I am trying to get a grasp on Cameron, Gelbach and Miller (2011) robust inference with multiway clustering. As I understand, bottom line is that ignoring clustering may result in standard errors ...
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cluster-robust standard errors are smaller than unclustered ones in fgls with cluster fixed effects

I'm currently working on some experimental data. The experimental design consists of two treatments. In each treatment, 20 subjects are randomly matched in pairs and participate to a simple game. The ...
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224 views

Few-clusters bias correction for cluster robust covariance matrix in random effects model

I'm currently working on some experimental data. Subjects are randomly assigned to one of two treatments. For each treatment I ran three sessions with 20 subjects each. In each session, participants ...
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1answer
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Stata error: “panels are not nested within clusters”

I have an unbalanced panel data set with more than 400,000 observations over 20 years. My panel variable is a person id and my time series variable is the year. The persons are from all over Germany ...
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Cluster robust standard errors in plm package [duplicate]

I am a beginner in R. I am using the plm package and I want to know the easiest way to get cluster robust standard errors for the fixed effects estimator. My data (called Mydata) is on poverty, GDP, ...
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645 views

Is it possible to cluster standard errors on time variables?

Somewhat weird question: But is it theoretically possible to have panel data (many i, many t) where standard errors are clustered on t?
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Clustered standard errors and robust standard errors

I was wondering if, when running a regression on panel data, clustered standard errors are already correcting for heteroskedasticity. Actually, I have run such a regression and detected ...
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panel data - within-group estimate - individual fixed effects retrieved

I am analyzing panel data. First, I have to decide whether to use a random or fixed effect estimator. The Hausman test suggests to use the fixed effect estimator (also named within group estimator). ...
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2answers
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Implausibly small standard error

I have data of operation success of many doctors. I estimated a regression using Stata with fix effects on the individual doctors. I first ran the regression using robust option. The resulted t value ...
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1answer
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Clustered standard errors and pooled OLS

Can someone please explain why clustered standard errors ensure that the error estimates of Pooled OLS results are appropriate?
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329 views

Clustered binary data

I have a binary outcome (success \ failure). I have 20 subjects, half of them gave 2 samples, the others just one, so I have 30 data points. All data points without any exceptions were success (1). ...
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394 views

Duration analysis of unemployment

I am trying to run a discrete duration model for analyzing (monthly) unemployment using survey data. I have household-level data, and as such I would like to control for the household effects in my ...
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What is the name for a regression undertaken with robust variance estimators for clustered data?

Just wondering what you call a regression undertaken with robust variance estimators for clustered data. Is it ok to say you have used OLS regression with robust variance estimators for clustered ...
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Why don't my cluster-robust (panel-robust) standard errors match those in Stata? (solved)

I'm trying to write my own code for cluster-robust (AKA panel-robust, AKA heteroskedasticity and serial-correlation-consistent) standard errors, so that I can make a couple of small extensions. But I ...
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Cluster-robust estimation versus Random Effects estimation

My dependent variable is the decision of individuals for a value between 1 and 8 in an economic experiment. Every individual repeated that decision 20 times. I want to regress individual ...
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2answers
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Cluster standard error _versus_ fixed effects

I am working with experimental data -correspondence test in the rental housing market-. On which ground can I choose between: F.E. for the region where the apt is and cluster s.e. on the day the ...
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1answer
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Clustered standard errors vs. multilevel modeling?

I've skimmed through several books (Raudenbush & Bryk, Snijders & Bosker, Gelman & Hill, etc.) and several articles (Gelman, Jusko, Primo & Jacobsmeier, etc.), and I still haven't ...
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Bootstrapping clusters in R

I am running a negative binomial regression of clinic counts in each county in the entire country (~3k counties). I'd like to at least partially account for the non-independence of neighboring ...
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1answer
808 views

Using F1_score to measure cluster validity

I have clustered over 4000 textual files, and now I want to check and evaluate clusters. I want to use F-measure (a mix of recall and precision). The formal definition of F1_score is: $$ \text{F-...
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1answer
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clustered-stratified random sampling

i've got questions about clustered-stratified random sampling. let's say I want to do a research in narcotics. the population that I will be working with is a combination of academics, students, and ...
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1answer
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Clustered (multilevel) data and fixed effects

I have a cross-sectional data set with about 8000 observations on child obesity (eg BMI). This data was collected in 8 countries and within schools (about 200 schools), i.e. observations are clustered ...
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2answers
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Dummies, clustered standard errors or both?

Relative novice here. I am running a regression in an observational setting in which Y is the outcome and D is the treatment indicator. Observations are drawn from 3 different geographic groups ...
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Wild cluster bootstrap seems really simple. Too simple. Am I missing someting?

I've been dealing with the problem of how to construct confidence intervals on penalized spline estimators in the presence of cluster-wise auto-correlation and heteroskedasticity. My previous thread ...
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Penalized spline confidence intervals based on cluster-sandwich VCV

This is my first post here, but I've benefited a lot from this forum's results popping up in google search results. I've been teaching myself semi-parametric regression using penalized splines. ...
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2answers
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Clustering high-dimensional sparse binary data

I am trying to cluster Facebook users based on their likes. I have two problems: First, since there is no dislike in Facebook all I have is having likes (1) for some items but for the rest of the ...
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How to correct for heteroskedasticity in fixed effects panel regression with correction for clustered standard error?

I am a student at RSM and I have a question regarding my regression analysis for my thesis as I have encountered issues I do not know how to deal with. I have performance data (dependent variable) of ...