robust_mixed {MLMusingR}

Cluster robust standard errors with degrees of freedom adjustments for lmerMod/lme objects

Description

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.

Usage

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

Arguments

m1

The lmerMod or lme model object.

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).

Value

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.

Author(s)

Francis Huang, [e-mail]

Bixi Zhang, [e-mail]

References

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)

Examples

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