On Thu, 6 Jan 2011, Jan Henckens wrote:
Hello,
I've got a question concerning the usage of robust standard errors in
regression using lm() and exporting the summaries to LaTeX using the
memisc-packages function mtable():
Is there any possibility to use robust errors which are obtained by vcovHC()
when generating the LateX-output by mtable()?
I tried to manipulate the lm-object by appending the "new" covariance matrix
but mtable seems to generate the summary itself since it is not possible to
call mtable(summary(lm1)).
I'm not a "memisc" user but had a quick look at the mtable() function. It
seems to rely on specification of some function getSummary() which
produces the numbers that are displayed.
By default the getSummary() method for "lm" objects is called which
contains a list element "coefs" with the coefficient table and confidence
intervals. So one quick hack would be to modify that to employ robust
standard errors:
mySummary <- function(obj, alpha = 0.05, ...) {
## get original summary
s <- getSummary(obj, alpha = alpha, ...)
## replace Wald tests of coefficients
s$coef[,1:4] <- coeftest(obj, vcov = vcovHC(obj))
## replace confidence intervals
crit <- qt(alpha/2, obj$df.residual)
s$coef[,5] <- s$coef[,1] + crit * s$coef[,2]
s$coef[,6] <- s$coef[,1] - crit * s$coef[,2]
return(s)
}
Then you can do
mtable(lm1, getSummary = mySummary)
and add also all the other options of mtable() that you would like to use.
hth,
Z
I'd like to obtain a table with the following structure (using standard
errors I already worked out how to archieve it):
Variable & Coeff. & robust S.E. & lower 95% KI & upper 95% KI \\
Var1 & x.22^(*) & (xxxxx) & [xxxxx & xxxxx] \\
.
.
.
Maybe someone has any suggestions how to implement this kind of table?
Best regards,
Jan Henckens
--
jan.henckens | jöllenbecker str. 58 | 33613 bielefeld
tel 0521-5251970
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