[R] extracting Pr>ltl from robcov/ols (Design)

[Mark Difford]

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
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> 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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