robust_mixed | R Documentation |

Function to compute the CR2/CR0 cluster robust standard errors (SE) with Bell and McCaffrey (2002) degrees of freedom (dof) adjustments. Suitable even with a low number of clusters. The model based (mb) and cluster robust standard errors are shown for comparison purposes.

```
robust_mixed(m1, digits = 3, type = "CR2", satt = TRUE, Gname = NULL)
```

`m1` |
The |

`digits` |
Number of decimal places to display. |

`type` |
Type of cluster robust standard error to use ("CR2" or "CR0"). |

`satt` |
If Satterthwaite degrees of freedom are to be computed (if not, between-within df are used). |

`Gname` |
Group/cluster name if more than two levels of clustering (does not work with lme). |

A data frame (`results`

) with the cluster robust adjustments with p-values.

`Estimate` |
The regression coefficient. |

`mb.se` |
The model-based (regular, unadjusted) SE. |

`cr.se` |
The cluster robust standard error. |

`df` |
degrees of freedom: Satterthwaite or between-within. |

`p.val` |
p-value using CR0/CR2 standard error. |

`stars` |
stars showing statistical significance. |

Francis Huang, huangf@missouri.edu

Bixi Zhang, bixizhang@missouri.edu

Bell, R., & McCaffrey, D. (2002). Bias reduction in standard errors for linear regression with multi-stage samples. Survey Methodology, 28, 169-182. (link)

Liang, K.Y., & Zeger, S. L. (1986). Longitudinal data analysis using generalized linear models. *Biometrika, 73*(1), 13-22.
(link)

```
require(lme4)
data(sch29, package = 'MLMusingR')
robust_mixed(lmer(math ~ male + minority + mses + mhmwk + (1|schid), data = sch29))
```

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