Question

我想知道植物发育得分是否取决于植物处理。所以我有以下实验设置：

治疗：“控制”或“治疗”
Plantpart：随后的植物部分。 “Root”，“Stem”或“Leaf”。
得分：植物部分的发育得分。解释变量，数字（连续）。

我还有两个因素被视为随机错误：

区块：4个街区（种植植物的地方）
Biological_Replicate：每株植物用于收集3个植物部分（根，茎，叶）。因此，给定植物的植物部分的得分不是独立的。对于处理植物和对照植物，每个块有3个生物学重复。

我定义了变量然后实现了模型：

library(lmerTest)
Score=Data$Score
Treatment=Data$Treatment
Biological_Replicate=as.factor(Data$Biological_Replicate)
Block=as.factor(Data$Block)
model<-lmer(Score~Treatment + (1|Biological_Replicate) + (1|Block), REML=FALSE)

尝试使用coef(summary(model))检索近似的p值产生了错误：

Model is not identifiable...
summary from lme4 is returned
some computational error has occurred in lmerTest

完整数据如下。问题是：代码和/或数据有什么问题？

Data<-structure(list(Treatment = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L), .Label = c("Control", "Treated"), class = "factor"), 
    Plantpart = structure(c(1L, 1L, 1L, 3L, 3L, 3L, 2L, 2L, 2L, 
    1L, 1L, 1L, 3L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 
    2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 1L, 
    3L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 2L, 2L, 2L, 
    1L, 1L, 1L, 3L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 
    2L, 2L, 2L), .Label = c("Leaf", "Root", "Stem"), class = "factor"), 
    Block = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 
    2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 
    4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
    3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4), Biological_Replicate = c(1, 
    2, 3, 1, 2, 3, 1, 2, 3, 4, 5, 6, 4, 5, 6, 4, 5, 6, 7, 8, 
    9, 7, 8, 9, 7, 8, 9, 10, 11, 12, 10, 11, 12, 10, 11, 12, 
    13, 14, 15, 13, 14, 15, 13, 14, 15, 16, 17, 18, 16, 17, 18, 
    16, 17, 18, 19, 20, 21, 19, 20, 21, 19, 20, 21, 22, 23, 24, 
    22, 23, 24, 22, 23, 24), Score = c(20628, 26610, 11410, 18755, 
    17366, 13228, 27011, 17558, 16512, 30945, 28606, 29092, 23262, 
    18306, 23034, 9627, 16193, 24391, 35197, 26092, 23789, 29900, 
    22649, 23548, 23868, 18495, 17204, 31750, 27496, 24687, 24115, 
    25911, 25076, 12472, 12267, 13120, 21580, 20697, 14854, 7190, 
    55734, 12194, 23853, 16762, 18322, 27582, 28056, 28497, 16156, 
    17680, 21789, 10137, 18122, 9786, 23866, 30878, 23101, 18104, 
    22276, 23694, 18534, 20743, 15460, 31997, 32559, 28969, 20408, 
    24503, 21395, 9925, 15407, 14717)), .Names = c("Treatment", 
"Plantpart", "Block", "Biological_Replicate", "Score"), row.names = c(NA, 
-72L), class = "data.frame")

lmerTest :: lmer - 模型不可识别

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