这里有一个分层模型的问题,想请教一下大家。
小弟的试验中,响应变量是RB,固定因素是treatment(四个水平为ck tr1 tr2 tr3),随机因素是year和block。我想分别比较ck和tr1 tr2 tr3的差异,即不关注tr1 tr2 tr3 三者之间的差异。
我用R做的,不过我想对于结果的解释应该跟软件无关。
我想请教一下:
(1)能否直接根据summary的结果,得出“tr1和ck的差异不显著,tr2 tr3和ck的差异显著“的结论?
(2)我能使用附图这样的方式来表示这种差异么?
(3)方法中我能用类似下面的话描述这种统计方法么?“ In the model, the RB under "ck" was set as the intercept, so for the other three conditions ("tr1","tr2" and "tr3"), 95% credibility interval that not overlapping zero indicate a significant difference from that in "ck" "
- library(MCMCglmm)
- fit1<-MCMCglmm(RB~Treatment,random=~Year+Block,data=tempRB)
- summary(fit1)
- Iterations = 3001:12991
- Thinning interval = 10
- Sample size = 1000
- DIC: -14.23551
- G-structure: ~Year
- post.mean l-95% CI u-95% CI eff.samp
- Year 0.3482 6.4e-56 0.1674 436
- ~Block
- post.mean l-95% CI u-95% CI eff.samp
- Block 0.0001119 1.156e-66 3.083e-08 798.7
- R-structure: ~units
- post.mean l-95% CI u-95% CI eff.samp
- units 0.02743 0.01134 0.048 114
- Location effects: RB ~ Treatment
- **post.mean l-95% CI u-95% CI eff.samp pMCMC
- (Intercept) 0.660959 0.391469 0.878285 1000 0.024 *
- Treatment_tr1 -0.004188 -0.207064 0.179150 1000 0.966
- Treatment_tr2 -0.387922 -0.586966 -0.186081 1085 <0.001 ***
- Treatment_tr3 -0.467356 -0.646885 -0.261730 1000 <0.001 *****
- ---
- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


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