Report estimates across different models
Combine(x, ...)list of model objects
additional arguments to lower-level functions
data(serotonin)
m1 <- lm(cau ~ age*gene1 + age*gene2,data=serotonin)
m2 <- lm(cau ~ age + gene1,data=serotonin)
m3 <- lm(cau ~ age*gene2,data=serotonin)
Combine(list(A=m1,B=m2,C=m3),fun=function(x)
c("_____"="",R2=" "%++%format(summary(x)$r.squared,digits=2)))
#> A B
#> (Intercept) 0.88 [0.85;0.91] p<0.001 0.89 [0.86;0.91] p<0.001
#> age 0.02 [-0.01;0.05] p=0.108 -0.01 [-0.02;0.01] p=0.414
#> gene1 -0.02 [-0.06;0.01] p=0.228 -0.02 [-0.06;0.01] p=0.219
#> gene2 0 [-0.03;0.04] p=0.93
#> age:gene1 -0.04 [-0.07;-0.01] p=0.019
#> age:gene2 -0.02 [-0.05;0.01] p=0.218
#> _____
#> R2 0.039 0.0083
#> C
#> (Intercept) 0.88 [0.85;0.9] p<0.001
#> age 0.01 [-0.02;0.03] p=0.549
#> gene1
#> gene2 0 [-0.03;0.04] p=0.99
#> age:gene1
#> age:gene2 -0.03 [-0.06;0.01] p=0.126
#> _____
#> R2 0.012