Clustered standard errors (or Liang-Zeger standard errors)[1] are measurements that estimate the standard error of a regression parameter in settings where observations may be subdivided into smaller-sized groups ("clusters") and where the sampling and/or treatment assignment is correlated within each group.[2][3] Clustered standard errors are widely used in a variety of applied econometric settings, including difference-in-differences[4] or experiments.[5]
Analogous to how Huber-White standard errors are consistent in the presence of heteroscedasticity and Newey–West standard errors are consistent in the presence of accurately-modeled autocorrelation, clustered standard errors are consistent in the presence of cluster-based sampling or treatment assignment. Clustered standard errors are often justified by possible correlation in modeling residuals within each cluster; while recent work suggests that this is not the precise justification behind clustering,[6] it may be pedagogically useful.
^Liang, Kung-Yee; Zeger, Scott L. (1986-04-01). "Longitudinal data analysis using generalized linear models". Biometrika. 73 (1): 13–22. doi:10.1093/biomet/73.1.13. ISSN 0006-3444.
^Cameron, A. Colin; Miller, Douglas L. (2015-03-31). "A Practitioner's Guide to Cluster-Robust Inference". Journal of Human Resources. 50 (2): 317–372. CiteSeerX 10.1.1.703.724. doi:10.3368/jhr.50.2.317. ISSN 0022-166X. S2CID 1296789.
^"ARE 212". Fiona Burlig. Retrieved 2020-07-05.
^Bertrand, Marianne; Duflo, Esther; Mullainathan, Sendhil (2004-02-01). "How Much Should We Trust Differences-In-Differences Estimates?". The Quarterly Journal of Economics. 119 (1): 249–275. doi:10.1162/003355304772839588. hdl:1721.1/63690. ISSN 0033-5533. S2CID 470667.
^Yixin Tang (2019-09-11). "Analyzing Switchback Experiments by Cluster Robust Standard Error to prevent false positive results". DoorDash Engineering Blog. Retrieved 2020-07-05.
^Abadie, Alberto; Athey, Susan; Imbens, Guido; Wooldridge, Jeffrey (2017-10-24). "When Should You Adjust Standard Errors for Clustering?". arXiv:1710.02926 [math.ST].
and 24 Related for: Clustered standard errors information
Clusteredstandarderrors (or Liang-Zeger standarderrors) are measurements that estimate the standarderror of a regression parameter in settings where...
sample means cluster more closely around the population mean. Therefore, the relationship between the standarderror of the mean and the standard deviation...
error in the findings). By convention, only effects more than two standarderrors away from a null expectation are considered "statistically significant"...
X_{i}} . Correlated errors that exist within subsets of the data or follow specific patterns can be handled using clusteredstandarderrors, geographic weighted...
maintenance, while the rest of the cluster takes on the load of that individual node. If you have a large number of computers clustered together, this lends itself...
type I errors and type II errors is widely used in medical science, biometrics and computer science.[clarification needed] Intuitively, type I errors can...
random-error-detecting/correcting and burst-error-detecting/correcting. Some codes can also be suitable for a mixture of random errors and burst errors. If...
interpreted as "the number of standarderrors away from the regression line." In regression analysis, the distinction between errors and residuals is subtle...
Gelbach and D. L. Miller (2008): Bootstrap-Based Improvements for Inference with ClusteredErrors. The Review of Economics and Statistics 90, pp. 414–427....
In statistics, mean absolute error (MAE) is a measure of errors between paired observations expressing the same phenomenon. Examples of Y versus X include...
Munitions may also have larger standard deviation of range errors than the standard deviation of azimuth (deflection) errors, resulting in an elliptical...
preliminaries, it is possible to investigate the effect of sample size on the standarderrors of the mean and median. The observed mean is 3.16, the observed raw...
being stored in order. Therefore, only one clustered index can be created on a given database table. Clustered indices can greatly increase overall speed...
Schiff et al. defined diagnostic error as any breakdown in the diagnostic process, including both errors of omission and errors of commission. Similarly, Singh...
the same cluster with the average distance to elements in other clusters. Objects with a high silhouette value are considered well clustered, objects...
In statistics, the standard score is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above...
include the effects of errors in the nearer steps, both systematic and statistical ones. The result of these propagating errors means that distances in...
random errors (a measure of statistical variability). Accuracy has two definitions, per ISO: More commonly, a description of systematic errors (a measure...
On the other hand, when the variance is small, the data in the set is clustered. Dispersion is contrasted with location or central tendency, and together...
which determines the number of clusters that maximizes efficiency while minimizing error by information-theoretic standards. The strategy of the algorithm...
used in the past. Nowadays, standard practice in econometrics is to include Heteroskedasticity-consistent standarderrors instead of using GLS, as GLS...
distribution Ergodic theory Ergodicity Error bar Error correction model Error function Errors and residuals in statistics Errors-in-variables models An Essay towards...
within the Db2 SQLCA block. SQLCODE is no longer part of the SQL-standard. The SQL-standard replaced SQLCODE by the more detailed SQLSTATE. The SQL communications...
Global Information