ldb (?),
>> I am trying to extract significance levels out of a robcov+ols call....
>> However, I can't figure out how to get to the significance
(Pr>ltl).
>> It is obviously calculating it because the call:
It's calculated in print.ols(). See extract below. To see the whole
function, do
print.ols
## Extract from print.ols in package Design
se <- sqrt(diag(x$var))
z <- x$coefficients/se
P <- 2 * (1 - pt(abs(z), rdf))
co <- cbind(x$coefficients, se, z, P)
dimnames(co) <- list(names(x$coefficients), c("Value",
"Std. Error",
"t", "Pr(>|t|)"))
print(co)
HTH, Mark.
ldb-5 wrote:>
> I am trying to extract significance levels out of a robcov+ols call.
>
> For background: I am analysing data where multiple measurements(2 per
> topic) were taken from individuals(36) on their emotional reaction
> (dependent variable) to various topics (3 topics). Because I have
> several emotions and a rotation to do on the topics, I'd like to have
> the results pumped into a nice table.
>
> answer<-robcov(ols(emotion ~ topic,x=TRUE,y=TRUE),individual)
>
>>From the robcov help it warns me:
>
>>Adjusted ols fits do not have the corrected standard errors printed with
print.ols. Use sqrt(diag(adjfit$var)) to get this, where adjfit is the
result of robcov.>
> So I can get to the standard error by:
>
> answer.se<-sqrt(diag(answer$var))
>
> I can get to the coefficients by:
>
> answer.co<-coefficients(answer)
>
> I can get to the t-values by:
>
> answer.t<-coefficients(answer)/ sqrt(diag(answer$var))#t-value
>
> However, I can't figure out how to get to the significance (Pr>ltl).
> It is obviously calculating it because the call:
>
> answer
>
> provides it, but I can't figure out where it is getting it from or how
> it is calculating.
>
> thanks for any help.
>
> ldb
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
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