clubSandwich: Cluster-Robust Variance Estimators for Linear Models

An R software package providing several cluster-robust variance estimators for linear regression models. It implements methods from Bell and McCaffrey (2002) and Pustejovsky and Tipton (2017), including bias-reduced linearization and small-sample corrections for hypothesis testing. The package author is James E. Pustejovsky.

Use Cases

• Correcting standard errors in regression models based on the cluster-robust variance estimators described.
• Testing single regression coefficients using Satterthwaite or saddle-point corrections mentioned in the description.
• Testing multiple-contrast hypotheses using an approximation to Hotelling's T-squared distribution as detailed.
• Estimating variance-covariance matrices for a variety of fitted model objects listed, including lm(), glm(), and lmer().

Strengths

• Implements specific, peer-reviewed statistical methods from Bell and McCaffrey (2002) and Pustejovsky and Tipton (2017).
• Compatible with a wide range of model-fitting functions from popular R packages, as listed in the description.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

James E. Pustejovsky

Collection Method

Software package development and statistical method implementation.

Time Range

null

Freshness

Last update date is unknown; freshness unverified.

Geography

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