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clubSandwich - MaRDI portal

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clubSandwich (Q27956)

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Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections
Language Label Description Also known as
English
clubSandwich
Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections

    Statements

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    0.5.8
    15 August 2022
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    0.2.1
    23 July 2016
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    0.2.2
    1 December 2016
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    0.2.3
    10 August 2017
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    0.3.0
    13 November 2017
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    0.3.1
    4 April 2018
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    0.3.2
    22 May 2018
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    0.3.3
    24 January 2019
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    0.3.4
    11 May 2019
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    0.3.5
    14 May 2019
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    0.4.0
    18 December 2019
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    0.4.1
    28 January 2020
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    0.4.2
    23 July 2020
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    0.5.0
    1 September 2020
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    0.5.1
    12 October 2020
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    0.5.2
    14 November 2020
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    0.5.3
    24 January 2021
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    0.5.4
    9 January 2022
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    0.5.5
    18 January 2022
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    0.5.6
    23 April 2022
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    0.5.7
    15 June 2022
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    0.5.9
    12 July 2023
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    0.5.10
    20 July 2023
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    20 July 2023
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    Provides several cluster-robust variance estimators (i.e., sandwich estimators) for ordinary and weighted least squares linear regression models, including the bias-reduced linearization estimator introduced by Bell and McCaffrey (2002) <https://www150.statcan.gc.ca/n1/pub/12-001-x/2002002/article/9058-eng.pdf> and developed further by Pustejovsky and Tipton (2017) <doi:10.1080/07350015.2016.1247004>. The package includes functions for estimating the variance- covariance matrix and for testing single- and multiple- contrast hypotheses based on Wald test statistics. Tests of single regression coefficients use Satterthwaite or saddle-point corrections. Tests of multiple- contrast hypotheses use an approximation to Hotelling's T-squared distribution. Methods are provided for a variety of fitted models, including lm() and mlm objects, glm(), geeglm() (from package 'geepack'), ivreg() (from package 'AER'), ivreg() (from package 'ivreg' when estimated by ordinary least squares), plm() (from package 'plm'), gls() and lme() (from 'nlme'), lmer() (from ‘lme4'), robu() (from ’robumeta'), and rma.uni() and rma.mv() (from 'metafor').
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    Identifiers