Entering edit mode
6.1 years ago
pierre.jorcin
•
0
Hi everyone,
I am struggling to compare models performance, to evaluate results from glm vs. gam models. Using the below formula, I am trying to evaluate ANOVA results for both models, but results indicators are different. How can I interpret them, individually first, then one vs. another ? best regards,
m <-mGAM@models$presence$gam$`1`@object
m
anova(m)
Family: binomial Link function: logit Estimated degrees of freedom: 8.88 6.42 6.50 6.18 4.71 1.00 3.11 2.46 7.54 total = 47.8 UBRE score: -0.3067535 Family: binomial Link function: logit Formula: presence ~ s(Chelsea_bio4_R) + s(Chelsea_bio9_R) + s(Chelsea_bio10_R) + s(Chelsea_bio14_R) + s(Chelsea_bio15_R) + s(Chelsea_bio16_R) + s(alt_R) + s(orient_R) + s(NDVI_july_R) Approximate significance of smooth terms: edf Ref.df Chi.sq p-value s(Chelsea_bio4_R) 8.882 8.994 102.044 < 2e-16 s(Chelsea_bio9_R) 6.422 7.270 36.608 8.97e-06 s(Chelsea_bio10_R) 6.501 6.774 66.955 1.52e-09 s(Chelsea_bio14_R) 6.184 7.099 26.832 0.00045 s(Chelsea_bio15_R) 4.707 5.858 8.455 0.20454 s(Chelsea_bio16_R) 1.000 1.000 3.855 0.04961 s(alt) 3.106 3.925 3.890 0.32081 s(orient_R) 2.457 3.064 9.847 0.02181 s(NDVI_july_R) 7.541 8.469 22.067 0.00554
m <-mGLM@models$presence$glm$`1`@object
m
anova(m)
Coefficients: (Intercept) Chelsea_bio4_R Chelsea_bio9_R Chelsea_bio10_R Chelsea_bio14_R Chelsea_bio15_R Chelsea_bio16_R -6.6081112 0.0037166 0.1217509 0.1836676 -0.0526189 -0.0024913 0.0064658 alt_R orient_R NDVI_july_R -0.0004764 0.0023634 -0.0002167 Degrees of Freedom: 2159 Total (i.e. Null); 2150 Residual Null Deviance: 2848 Residual Deviance: 1782 AIC: 1802 Analysis of Deviance Table Model: binomial, link: logit Response: presence Terms added sequentially (first to last) Df Deviance Resid. Df Resid. Dev NULL 2159 2847.5 Chelsea_bio4_R 1 1.02 2158 2846.5 Chelsea_bio9_R 1 704.34 2157 2142.2 Chelsea_bio10_R 1 196.65 2156 1945.5 Chelsea_bio14_R 1 103.93 2155 1841.6 Chelsea_bio15_R 1 24.30 2154 1817.3 Chelsea_bio16_R 1 3.82 2153 1813.5 alt_R 1 0.57 2152 1812.9 orient_R 1 15.17 2151 1797.7 NDVI_july_R 1 15.26 2150 1782.5
I have tried to format your post to make it more readable, I hope I didn't delete information in the process.
Your question is more suited to Cross Validated. Be sure to do some reading before posting there:
How to compare GLM and GAM models
GAM versus GLM: same fit, different significance of predictors
When to use a GAM vs GLM
ANOVA to compare models
comparing models in R