Why there is no p-value from likelihood ratio test using anova in GAM model fitting?
The simpler model has the lower deviance (marginally), so there is nothing to test here. This can happen with maximum penalized likelihood estimators, even though the models are nested (especially if the smoothing parameters are selected automatically). Are you using gam:gam or mgcv:gam (and which version numbers)? best, Simon
On Tuesday 28 April 2009 12:38, willow1980 wrote:
Hello, everybody, There is the first time for me to post a question, because I really cannot find answer from books, websites or my colleagues. Thank you in advance for your help! I am running likelihood ratio test to find if the simpler model is not significant from more complicated model. However, when I run LRT to compare them, the test did not return F value and p-value for me. What's the reason? How can I get such important information? #################################################### Analysis of Deviance Table Model 1: sum_surv15 ~ s(FLBS) + s(byear) + s(FLBS, byear) Model 2: sum_surv15 ~ s(FLBS) + SES + s(byear) + s(FLBS, byear) Resid. Df Resid. Dev Df Deviance F Pr(>F) 1 1202.21094 601.27 2 1201.43848 601.29 0.77246 -0.02 #################################################### Thank you very much! Jianghua Liu, University of Sheffield
> Simon Wood, Mathematical Sciences, University of Bath, Bath, BA2 7AY UK > +44 1225 386603 www.maths.bath.ac.uk/~sw283