test data frame:
> foo
x y z
1 0.191 0.324 0.620
2 0.229 0.302 0.648
3 0.191 0.351 0.626
4 0.229 0.324 0.630
5 0.152 0.374 0.656
6 0.191 0.295 0.609
7 0.229 0.267 0.665
8 0.152 0.353 0.657
9 0.152 0.355 0.655
Two linear models:
model1 <- lm(z~polym(x,y,degree = 1),data=foo)
model2 <- lm(z~polym(x,y,degree = 2),data=foo)
ANOVA for the two models returns:
> anova(model1,model2)
Analysis of Variance Table
Model 1: z ~ polym(x, y, degree = 1)
Model 2: z ~ polym(x, y, degree = 2)
Res.Df RSS Df Sum of Sq F Pr(>F)
1 6 0.002988
2 3 0.000169 3 0.00282 16.6 0.023 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Why the single *
? 0.05 > 0.023 > 0.01, so shouldn't it print a .
symbol?
There is nothing wrong.
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
means:
annotation p-value significance level
*** [0, 0.001] 0.001
** (0.001, 0.01] 0.01
* (0.01, 0.05] 0.05
. (0.05, 0.1] 0.1
(0.1, 1] 1
0.023 is within (0.01, 0.05]
, so it should be annotated by *
.