[英]R: Analyse trends in mixed-effects model
I have a variable yi
that represents a treatment effect over time nyears
for a bunch of different studies ( Site
). 我有一个变量
yi
,代表了一系列不同研究( Site
)随时间推移nyears
的治疗效果。 There are also two grouping factors with two levels each: N
(Nhigh/Nlow) and Myc
(AM/ECM). 还有两个分组因子,每个分组因子具有两个级别:
N
(Nhigh / Nlow)和Myc
(AM / ECM)。 I need to know if yi
shows a significant positive or negative trend over time nyears
, and if the trends changes among subgroups N
x Myc
. 我需要知道
yi
在过去nyears
是否显示出显着的正或负趋势,以及该趋势是否在子组N
x Myc
之间变化。
The mixed-effects models shows a significant triple interaction nyears
* N
* Myc
混合效应模型显示显著三重互动
nyears
* N
* Myc
library(lme4)
library(car)
> mod <- lmer(yi ~ N*Myc*nyears + (1|Site), data = df)
> Anova(mod)
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: yi
Chisq Df Pr(>Chisq)
N 0.7468 1 0.387489
Myc 0.0875 1 0.767403
nyears 1.1217 1 0.289559
N:Myc 0.5428 1 0.461272
N:nyears 2.2371 1 0.134733
Myc:nyears 0.6318 1 0.426691
N:Myc:nyears 10.8108 1 0.001009 **
How can I now find out the sign of the slope and significance for each of the 4 subgroups? 我现在如何找出4个子组中每个子组的斜率和重要性的符号?
Thanks 谢谢
The value of the slope (on nyears
, right?) is given by 斜率的值(以
nyears
,对吗?)由
nyears
nyears + N:nyears
nyears + Myc:nyears
nyears + Myc:nyears + N:Myc:nyears
for the four respective groups. 四个组。 (Are
N
and Myc
numeric 0/1? They don't look like factors, judging by the output. If they aren't 0/1 the recode.) (
N
和Myc
数字是否为0/1?根据输出判断,它们看起来不是因子。如果不是0/1,则重新编码。)
For significance testing of the slopes, either use linearHypothesis
in the CAR
package; 对于斜率的显着性检验,可以在
CAR
包装中使用linearHypothesis
。 or you could use eg waldtest
in package lmtest
; 或者您可以在
lmtest
软件包中使用waldtest
; or rewrite your model so that nyears
is the coefficient of interest for each of the four groups. 或重写您的模型,使
nyears
是四个组中每个组的兴趣系数。 (For example, set Myc
equal to 1 minus its old value, if it was a 0/1 dummie.) (例如,将
Myc
设置为1减去它的旧值(如果它是0/1的假人)。)
I would use the nlme
package to code the mixed effects model and then check the output using summary
. 我将使用
nlme
包对混合效果模型进行编码,然后使用summary
检查输出。 This will report slopes, signs and p values. 这将报告斜率,符号和p值。
require(nlme)
m1<- lme(yi ~ N*Myc*nyears, random= ~1|Site, data=df)
summary(m1)
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