I've been using the fantastic package texreg to produce high-quality HTML tables from lme4 models. Unfortunately, by default, texreg creates confidence intervals, rather than standard errors, under the coefficients for models from lme4 (see page 17 of the JSS paper).
As an example:
library(lme4)
library(texreg)
screenreg(lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
produces
Computing profile confidence intervals ...
Computing confidence intervals at a confidence level of 0.95. Use argument "method = 'boot'" for bootstrapped CIs.
===============================================
Model 1
-----------------------------------------------
(Intercept) 251.41 *
[237.68; 265.13]
Days 10.47 *
[ 7.36; 13.58]
-----------------------------------------------
AIC 1755.63
BIC 1774.79
Log Likelihood -871.81
Deviance 1743.63
Num. obs. 180
Num. groups: Subject 18
Variance: Subject.(Intercept) 612.09
Variance: Subject.Days 35.07
Variance: Residual 654.94
===============================================
* 0 outside the confidence interval
And I would prefer to see something like this:
Computing profile confidence intervals ...
Computing confidence intervals at a confidence level of 0.95. Use argument "method = 'boot'" for bootstrapped CIs.
===============================================
Model 1
-----------------------------------------------
(Intercept) 251.41 *
(24.74)
Days 10.47 *
(5.92)
-----------------------------------------------
[output truncated for clarity]
Is there a way to over-ride this behavior? Using the ci.force = FALSE option doesn't work, as far as I can tell.
I'm sticking with texreg, rather than one of the other packages like stargazer, because texreg allows me to group coefficients into meaningful groups.
Thanks in advance for your help!
(UPDATE: edited to include an example)
Using naive=TRUE gets close to what you want ...
library(lme4); library(texreg)
fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)
screenreg(fm1,naive=TRUE)
## ==========================================
## Model 1
## ------------------------------------------
## (Intercept) 251.41 ***
## (6.82)
## Days 10.47 ***
## (1.55)
## ------------------------------------------
## [etc.]
I don't know where you got your values of 24.94, 5.92 from ... ?
sqrt(diag(vcov(fm1)))
## [1] 6.824556 1.545789
cc <- confint(fm1,which="beta_")
apply(cc,1,diff)/3.84
## (Intercept) Days
## 7.14813 1.61908
The implied standard errors based on scaling the profile confidence intervals are a little bit wider, but not hugely different.
What I don't know how to do easily is to get significance tests/stars based on profile confidence intervals while still getting standard errors in the table. According to the ci.test entry in ?texreg,
texreg prints a single star if the confidence intervals don't include zeroCollected from the Internet
Please contact [email protected] to delete if infringement.
Comments