lme4 error: boundary (singular) fit: see ?isSingular

Question

I am trying to run lme4 package in R. I have 10 Lines in total with four plants for each line in each of the two replications. But some of the plants died and there are some missing values. Weight is the response variable. Here are some lines from the data:

Line    Rep Weight  PLANT
Line 1  1   NA  1
Line 1  1   NA  2
Line 1  1   NA  3
Line 1  1   NA  4
Line 2  1   26  1
Line 2  1   26  2
Line 2  1   26  3
Line 2  1   27  4
Line 1  2   26  1
Line 1  2   28  2
Line 1  2   26  3
Line 1  2   25  4
Line 2  2   24  1
Line 2  2   26  2
Line 2  2   25  3
Line 2  2   NA  4

I want to run linear mixed model using lme4 package so I tried running:

lme4 <- lmer(Weight ~ 1 + (1|Rep:Plant), data=Data)

But I got an error:

boundary (singular) fit: see ?isSingular

> dput(Data)
structure(list(Line = c("Line 1", "Line 1", "Line 1", "Line 1", 
"Line 2", "Line 2", "Line 2", "Line 2", "Line 1", "Line 1", "Line 1", 
"Line 1", "Line 2", "Line 2", "Line 2", "Line 2"), Rep = c(1, 
1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2), Weight = c(NA, 
NA, NA, NA, 26, 26, 26, 27, 26, 28, 26, 25, 24, 26, 25, NA), 
    PLANT = c(1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4)), row.names = c(NA, 
-16L), class = c("tbl_df", "tbl", "data.frame"))

I am using it for the first time and I am not sure about the error. I will appreciate any help!

StupidWolf · Accepted Answer

Your model did fit, but it generated that warning because your random effects are very small. You can read more about this in this post or the help page

Let us look at your data:

ggplot(Data,aes(x=PLANT,y=Weight,col=Rep)) + geom_jitter() + geom_boxplot(alpha=0.2) + facet_wrap(~Rep)

enter image description here

The effects of PLANT and in combination with Rep is extremely small. Let's look at the fitted model:

fit = lmer(Weight ~ 1 + (1|PLANT:Rep),data=Data)
boundary (singular) fit: see ?isSingular
ranef(fit)
$`PLANT:Rep`
    (Intercept)
1:1           0
1:2           0
2:1           0
2:2           0
3:1           0
3:2           0
4:1           0
4:2           0

This is exactly what happened. So we can try to account for some other effects and we still see very small coefficients:

fit = lmer(Weight ~ Line + (1|Rep:PLANT),data=Data)
ranef(fit)
$`Rep:PLANT`
      (Intercept)
1:1  1.397563e-19
1:2  2.811371e-19
1:3  8.112169e-20
1:4  1.813251e-19
2:1 -1.725964e-19
2:2 -2.463986e-20
2:3 -2.027357e-19
2:4 -2.833681e-19

The takehome message is, there's no really systematic effect coming from PLANT, so you don't need to specify a highly complicated model, do something like:

fit = lmer(Weight ~ Line + (1|Rep),data=Data)

The data in case anyone is interested:

Data = structure(list(Line = structure(c(1L, 1L, 1L, 1L, 12L, 12L, 12L, 
12L, 23L, 23L, 23L, 23L, 34L, 34L, 34L, 34L, 45L, 45L, 45L, 45L, 
56L, 56L, 56L, 56L, 65L, 65L, 65L, 65L, 66L, 66L, 66L, 66L, 67L, 
67L, 67L, 67L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 
5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 
9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 13L, 
13L, 13L, 13L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 16L, 16L, 
16L, 16L, 8L, 8L, 8L, 8L, 66L, 66L, 66L, 66L, 17L, 17L, 17L, 
17L, 18L, 18L, 18L, 18L, 9L, 9L, 9L, 9L, 19L, 19L, 19L, 19L, 
20L, 20L, 20L, 20L, 21L, 21L, 21L, 21L, 22L, 22L, 22L, 22L, 24L, 
24L, 24L, 24L, 25L, 25L, 25L, 25L, 2L, 2L, 2L, 2L, 26L, 26L, 
26L, 26L, 27L, 27L, 27L, 27L, 10L, 10L, 10L, 10L, 28L, 28L, 28L, 
28L, 29L, 29L, 29L, 29L, 30L, 30L, 30L, 30L, 31L, 31L, 31L, 31L, 
67L, 67L, 67L, 67L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 33L, 
33L, 33L, 33L, 35L, 35L, 35L, 35L, 36L, 36L, 36L, 36L, 37L, 37L, 
37L, 37L, 38L, 38L, 38L, 38L, 39L, 39L, 39L, 39L, 40L, 40L, 40L, 
40L, 25L, 25L, 25L, 25L, 19L, 19L, 19L, 19L, 24L, 24L, 24L, 24L, 
41L, 41L, 41L, 41L, 42L, 42L, 42L, 42L, 30L, 30L, 30L, 30L, 43L, 
43L, 43L, 43L, 44L, 44L, 44L, 44L, 22L, 22L, 22L, 22L, 46L, 46L, 
46L, 46L, 47L, 47L, 47L, 47L, 17L, 17L, 17L, 17L, 48L, 48L, 48L, 
48L, 49L, 49L, 49L, 49L, 27L, 27L, 27L, 27L, 23L, 23L, 23L, 23L, 
50L, 50L, 50L, 50L, 51L, 51L, 51L, 51L, 52L, 52L, 52L, 52L, 41L, 
41L, 41L, 41L, 7L, 7L, 7L, 7L, 46L, 46L, 46L, 46L, 11L, 11L, 
11L, 11L, 33L, 33L, 33L, 33L, 53L, 53L, 53L, 53L, 54L, 54L, 54L, 
54L, 13L, 13L, 13L, 13L, 38L, 38L, 38L, 38L, 4L, 4L, 4L, 4L, 
37L, 37L, 37L, 37L, 55L, 55L, 55L, 55L, 57L, 57L, 57L, 57L, 44L, 
44L, 44L, 44L, 58L, 58L, 58L, 58L, 59L, 59L, 59L, 59L, 12L, 12L, 
12L, 12L, 47L, 47L, 47L, 47L, 48L, 48L, 48L, 48L, 60L, 60L, 60L, 
60L, 21L, 21L, 21L, 21L, 18L, 18L, 18L, 18L, 28L, 28L, 28L, 28L, 
26L, 26L, 26L, 26L, 61L, 61L, 61L, 61L, 31L, 31L, 31L, 31L, 59L, 
59L, 59L, 59L, 52L, 52L, 52L, 52L, 29L, 29L, 29L, 29L, 62L, 62L, 
62L, 62L, 63L, 63L, 63L, 63L, 54L, 54L, 54L, 54L, 55L, 55L, 55L, 
55L, 53L, 53L, 53L, 53L, 51L, 51L, 51L, 51L, 50L, 50L, 50L, 50L, 
64L, 64L, 64L, 64L, 20L, 20L, 20L, 20L, 58L, 58L, 58L, 58L, 16L, 
16L, 16L, 16L, 57L, 57L, 57L, 57L, 14L, 14L, 14L, 14L, 63L, 63L, 
63L, 63L, 64L, 64L, 64L, 64L, 61L, 61L, 61L, 61L, 36L, 36L, 36L, 
36L, 40L, 40L, 40L, 40L, 6L, 6L, 6L, 6L, 39L, 39L, 39L, 39L, 
45L, 45L, 45L, 45L, 15L, 15L, 15L, 15L, 1L, 1L, 1L, 1L, 42L, 
42L, 42L, 42L, 43L, 43L, 43L, 43L, 65L, 65L, 65L, 65L, 49L, 49L, 
49L, 49L, 56L, 56L, 56L, 56L, 3L, 3L, 3L, 3L, 62L, 62L, 62L, 
62L, 35L, 35L, 35L, 35L, 5L, 5L, 5L, 5L, 60L, 60L, 60L, 60L, 
34L, 34L, 34L, 34L), .Label = c("Line1", "Line10", "Line11", 
"Line12", "Line13", "Line14", "Line15", "Line16", "Line17", "Line18", 
"Line19", "Line2", "Line20", "Line21", "Line22", "Line23", "Line24", 
"Line25", "Line26", "Line27", "Line28", "Line29", "Line3", "Line30", 
"Line31", "Line32", "Line33", "Line34", "Line35", "Line36", "Line37", 
"Line38", "Line39", "Line4", "Line40", "Line41", "Line42", "Line43", 
"Line44", "Line45", "Line46", "Line47", "Line48", "Line49", "Line5", 
"Line50", "Line51", "Line52", "Line53", "Line54", "Line55", "Line56", 
"Line57", "Line58", "Line59", "Line6", "Line60", "Line61", "Line62", 
"Line63", "Line64", "Line65", "Line66", "Line67", "Line7", "Line8", 
"Line9"), class = "factor"), Rep = 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, 
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, 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, 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, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 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, 
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, 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, 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, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 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, 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, 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, 
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, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L), .Label = c("1", "2"), class = "factor"), Weight = c(NA, 
NA, NA, NA, 26L, 26L, 26L, 27L, NA, NA, NA, NA, 26L, 28L, 26L, 
25L, 22L, 17L, 20L, 20L, 28L, 20L, 27L, 26L, 22L, 25L, 21L, 25L, 
18L, 18L, 19L, 18L, 24L, 28L, 23L, 30L, 29L, 25L, 26L, 27L, NA, 
NA, NA, NA, 29L, 30L, 29L, 30L, NA, NA, NA, NA, 33L, NA, NA, 
NA, 21L, 23L, 18L, 23L, 32L, 29L, 30L, 30L, 18L, 19L, 21L, 21L, 
25L, 25L, 25L, 26L, 26L, 27L, NA, NA, 29L, 29L, 27L, 29L, 26L, 
NA, NA, NA, 26L, 20L, 23L, 27L, NA, NA, NA, NA, 32L, 32L, 30L, 
30L, 20L, 20L, 20L, 19L, 22L, 21L, 22L, 22L, 24L, 23L, 23L, 25L, 
20L, 25L, NA, NA, 27L, 26L, NA, NA, NA, NA, NA, NA, 30L, 28L, 
NA, NA, 25L, 26L, 27L, 26L, NA, NA, NA, NA, 20L, 19L, NA, NA, 
19L, 27L, 26L, 29L, 26L, 29L, 31L, 29L, 25L, 25L, 24L, 25L, 26L, 
25L, 26L, 26L, 25L, 24L, 24L, 28L, 22L, 26L, 24L, 28L, 29L, 30L, 
26L, NA, NA, NA, NA, NA, 26L, 24L, 24L, 24L, NA, NA, NA, NA, 
NA, NA, NA, NA, 30L, 30L, 30L, 31L, 24L, 25L, 28L, 22L, 28L, 
31L, 30L, NA, 31L, 30L, 29L, 25L, 25L, 22L, 24L, 20L, 30L, 30L, 
30L, 29L, 26L, 32L, 28L, 29L, 20L, 15L, 15L, 11L, 25L, 24L, 24L, 
24L, 26L, 29L, 31L, 30L, 24L, 28L, 20L, 22L, 29L, 26L, 26L, 28L, 
27L, 27L, 27L, 26L, 21L, 22L, 21L, NA, 28L, 29L, 24L, 24L, 28L, 
29L, 28L, 27L, 28L, 29L, 27L, 29L, NA, NA, NA, NA, 22L, 26L, 
21L, 21L, 26L, 30L, 28L, 30L, 27L, 26L, 28L, 26L, 25L, 25L, 26L, 
26L, 27L, 26L, 23L, 29L, NA, NA, NA, NA, 27L, 23L, 29L, 23L, 
28L, 29L, 28L, 26L, 20L, NA, NA, NA, 28L, 23L, 26L, 21L, 28L, 
26L, 26L, 29L, 20L, 27L, 20L, 26L, 29L, 26L, 28L, 28L, 30L, 27L, 
NA, NA, 26L, 21L, 26L, 25L, 27L, 26L, 27L, 24L, 25L, 20L, 21L, 
20L, 25L, 25L, 31L, 24L, 29L, 28L, 31L, 27L, 25L, 28L, 26L, 26L, 
NA, NA, NA, NA, 24L, 25L, 23L, 27L, 20L, 26L, 25L, 25L, 29L, 
28L, 29L, 29L, 26L, 27L, 25L, 28L, NA, NA, NA, NA, 26L, 28L, 
NA, NA, 21L, 20L, 31L, 25L, 31L, 28L, 30L, 29L, 23L, 25L, 24L, 
28L, 25L, 22L, 25L, 25L, 28L, 29L, 28L, 29L, 26L, 24L, 25L, 26L, 
29L, 27L, NA, NA, 26L, 29L, 29L, 30L, 25L, 24L, 25L, 24L, 28L, 
25L, 29L, 28L, 24L, 24L, 24L, 24L, 28L, 30L, 27L, 27L, 26L, 25L, 
25L, 25L, 25L, 25L, 28L, 25L, 25L, 30L, 28L, 25L, 22L, 24L, 25L, 
24L, NA, NA, NA, NA, 5L, 7L, 4L, 5L, 21L, 20L, 22L, 24L, 25L, 
27L, 25L, 28L, 32L, 31L, NA, NA, 19L, 26L, 20L, NA, 26L, 26L, 
30L, 25L, 28L, 31L, 30L, 26L, 5L, 8L, 4L, 8L, 25L, 25L, 28L, 
25L, 28L, 28L, 27L, 26L, 30L, 27L, 27L, 24L, 32L, 29L, 31L, 25L, 
30L, 30L, 27L, 28L, 16L, 20L, 16L, 21L, 25L, 22L, 25L, 20L, 24L, 
25L, 18L, 25L, 25L, 26L, 29L, 29L, 21L, 20L, 22L, 21L, 19L, 22L, 
19L, 21L, 28L, 25L, 26L, 24L, 28L, 26L, 24L, 25L, NA, NA, NA, 
NA, 25L, NA, NA, NA, 23L, 21L, 19L, 23L, 25L, 24L, 25L, NA, 22L, 
30L, 29L, 26L, 25L, 25L, 24L, 24L), PLANT = structure(c(1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 
3L, 4L, 1L, 2L, 3L, 4L), .Label = c("1", "2", "3", "4"), class = "factor"), 
    X = structure(c(4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 
    6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 
    5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 
    2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 
    4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 
    6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 
    5L, 6L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 
    7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 
    3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 
    1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 
    8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 
    7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 
    4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 
    6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 
    5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 
    2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 
    4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 
    6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 
    5L, 6L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 
    7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 
    3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 
    1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 
    8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 
    7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 
    3L, 7L, 8L, 1L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 
    6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 
    5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 
    2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 
    4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 
    6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 5L, 6L, 4L, 2L, 
    5L, 6L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 
    7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 
    3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 
    1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 
    8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 
    7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L, 3L, 7L, 8L, 1L
    ), .Label = c("24", "12", "21", "11", "13", "14", "22", "23"
    ), class = "factor")), row.names = c(NA, -536L), class = "data.frame")

lme4 error: boundary (singular) fit: see ?isSingular

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lme4

Jessica

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StupidWolf

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lme4 error: boundary (singular) fit: see ?isSingular

Tags:

r

lme4

Jessica

1 Answers

StupidWolf

Related questions

Recent Activity

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