Greetings, I know that p-value estimation in mixed models are somewhat controversial at the moment, but I am simply curious how one extracts p-values for the fixed factors from an lme object (using nlme)? The summary() gives the desired p-values; all I want to do is access them. The names() command shows the returned values (e.g., fitted, residuals) for many components of the model, but I can't seem to access the p-values. Thank you in advance!
Extracting p-values from an lme object (any help would be appreciated)
4 messages · Ben Zuckerberg, Ben Bolker, Adam D. I. Kramer +1 more
Ben Zuckerberg wrote:
Greetings, I know that p-value estimation in mixed models are somewhat controversial at the moment, but I am simply curious how one extracts p-values for the fixed factors from an lme object (using nlme)? The summary() gives the desired p-values; all I want to do is access them. The names() command shows the returned values (e.g., fitted, residuals) for many components of the model, but I can't seem to access the p-values. Thank you in advance!
library(nlme) example(lme) summary(fm1)$tTable[,"p-value"]
Ben Bolker Associate professor, Biology Dep't, Univ. of Florida bolker at ufl.edu / www.zoology.ufl.edu/bolker GPG key: www.zoology.ufl.edu/bolker/benbolker-publickey.asc
On Wed, 25 Nov 2009, Ben Bolker wrote:
Ben Zuckerberg wrote:
I know that p-value estimation in mixed models are somewhat controversial at the moment, but I am simply curious how one extracts p-values for the fixed factors from an lme object (using nlme)? The summary() gives the desired p-values; all I want to do is access them. The names() command shows the returned values (e.g., fitted, residuals) for many components of the model, but I can't seem to access the p-values. Thank you in advance!
library(nlme) example(lme) summary(fm1)$tTable[,"p-value"]
Or perhaps more simply, pt(t, df, lower.tail) gives you the p-value associated with a given t-value and its degrees of freedom. lower.tail is whether you want the p below the t-value (usually you want this when p is negative), or above. Multiply by 2 for a 2-tailed test. summary() is almost certainly just calling pt(). --Adam
Adam, I'm sorry, I must jump in here. See responses to specific points below. Regards, Rob Kushler
Adam D. I. Kramer wrote:
On Wed, 25 Nov 2009, Ben Bolker wrote:
Ben Zuckerberg wrote:
I know that p-value estimation in mixed models are somewhat controversial at the moment, but I am simply curious how one extracts p-values for the fixed factors from an lme object (using nlme)? The summary() gives the desired p-values; all I want to do is access them. The names() command shows the returned values (e.g., fitted, residuals) for many components of the model, but I can't seem to access the p-values. Thank you in advance!
library(nlme) example(lme) summary(fm1)$tTable[,"p-value"]
Or perhaps more simply,
It's true that calling "pt" is a simple way to *compute* the
p-values, but the question was how to *extract* them. In general
the ability to manipulate objects is a key advantage of R.
pt(t, df, lower.tail) gives you the p-value associated with a given t-value and its degrees of freedom. lower.tail is whether you want the p below the t-value (usually you want this when p is negative), or above.
I think you mean "when t is negative" - but that's still not correct.
You want "lower=TRUE" when the alternative hypothesis Ha says "<" and
"lower=FALSE" when Ha says ">", regardless of the sign of t.
Multiply by 2 for a 2-tailed test.
Actually you need "2*pt(-abs(t), df, lower=TRUE)" to ensure a
correct two-sided p-value.
summary() is almost certainly just calling pt(). --Adam
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