> Question. Am I correct that p = .126 above can be taken as the
> p-value associated with the random effect?
- Yes. See
http://biomet.oxfordjournals.org/content/100/4/1005.abstract
for details of the approximate test used.
On 03/12/13 20:09, William Shadish wrote:
Dear R-helpers,
I would like to test whether a random effect is significant when
implemented with bs="re" in mgcv gam. For example, if I run:
M3b <- gam(DVY ~ s(SessIDX, fTX, bs = "re") + factor(TX),
data = PCP,
family = quasipoisson(link="log"), method="REML")
summary(M3b,all.p=TRUE)
gam.vcomp(M3b)
I obtain the the following output:
> summary(M3b,all.p=TRUE)
Family: quasipoisson
Link function: log
Formula:
DVY ~ s(SessIDX, fTX, bs = "re") + factor(TX)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.3282 0.2244 5.920 2.74e-07 ***
factor(TX)1 -1.0546 0.7210 -1.463 0.15
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(SessIDX,fTX) 1.052 2 1.138 0.126
R-sq.(adj) = 0.388 Deviance explained = 39.5%
REML score = 37.67 Scale est. = 1.4172 n = 54
> gam.vcomp(M3b)
Standard deviations and 0.95 confidence intervals:
std.dev lower upper
s(SessIDX,fTX) 0.07842742 0.01095655 0.5613865
scale 1.19029872 0.97816911 1.4484316
Rank: 2/2
Question. Am I correct that p = .126 above can be taken as the p-value
associated with the random effect?
Thanks.
Will Shadish
--
Simon Wood, Mathematical Science, University of Bath BA2 7AY UK
+44 (0)1225 386603 http://people.bath.ac.uk/sw283
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