我正在比较两个模型,以查看特定交互(会话组)是否重要。Mod1 是完整模型,Mod2 是完整模型减去会话组交互。
mod1 = lmer(accuracy ~ session + trialtype + group + session*trialtype +
session*group + session*group*trialtype + trialtype*group +
(1+trialtype|subject), data=data, REML=FALSE)
mod2 = lmer(accuracy ~ session + trialtype + group + session*trialtype +
session*group*trialtype + trialtype*group + (1+trialtype|subject),
data=data, REML=FALSE)
这是我的相同输出:
Data: data
Models:
mod1: accuracy ~ session + trialtype + group + session * trialtype +
mod1: session * group + session * group * trialtype + trialtype *
mod1: group + (1 + trialtype | subject)
mod2: accuracy ~ session + trialtype + group + session * trialtype +
mod2: session * group * trialtype + trialtype * group + (1 + trialtype
|
mod2: subject)
Df AIC BIC logLik deviance Chisq Chi Df Pr(>Chisq)
mod1 27 4026.4 4150.3 -1986.2 3972.4
mod2 27 4026.4 4150.3 -1986.2 3972.4 0 0 1
代码有问题,我只是想不通。此外,在查看主要效果/交互时,这是比较 2 个模型的正确方法吗?我从来没有上过传销课程,所以我一直在自学。
先感谢您!
另外:如果有帮助,这里是我的数据的一个子集,如建议的那样:
subject accuracy group session trialtype
1 5 1.0000000 1 2 BX
2 93 0.8000000 2 2 BX
3 12 0.8000000 2 2 BY
4 85 1.0000000 3 1 BX
5 21 1.0000000 3 2 AX
6 54 0.9900000 2 2 AX
7 2 0.8000000 1 1 BY
8 36 0.9142857 2 1 BX
9 1 1.0000000 1 2 AY
10 4 0.7900000 1 2 BY