linear mixed model using lmer

Dear all, I have this simple dataset to measure the yeild of a crop collected in 2 batches (attached). when I ran a simple inear mixed model using lmer to estimate within-batch and between-batch variability, the between-batch variability is 0. The run showed that data is singular. Does anyone know why the data is singular and what's the reason for 0 variability? is it because the dataset only has 2 batches?

daty<-read.table("datx.txt",sep='\t',header=T,row.names=NULL)
library(lme4)> lmer(yield~1+(1|batch),daty)

boundary (singular) fit: see ?isSingular
Linear mixed model fit by REML ['lmerMod']
Formula: yield ~ 1 + (1 | batch)
? ?Data: daty
REML criterion at convergence: 115.6358
Random effects:
?Groups? ?Name? ? ? ? Std.Dev.
?batch? ? (Intercept) 0.000? ?
?Residual? ? ? ? ? ? ?2.789? ?
Number of obs: 24, groups:? batch, 2
Fixed Effects:
(Intercept)??
? ? ? 5.788??

Thanks!
John

Dear all, I have this simple dataset to measure the yeild of a crop collected in 2 batches (attached). when I ran a simple inear mixed model using lmer to estimate within-batch and between-batch variability, the between-batch variability is 0. The run showed that data is singular. Does anyone know why the data is singular and what's the reason for 0 variability? is it because the dataset only has 2 batches?

daty<-read.table("datx.txt",sep='\t',header=T,row.names=NULL)
library(lme4)> lmer(yield~1+(1|batch),daty)

boundary (singular) fit: see ?isSingular
Linear mixed model fit by REML ['lmerMod']
Formula: yield ~ 1 + (1 | batch)
? ?Data: daty
REML criterion at convergence: 115.6358
Random effects:
?Groups? ?Name? ? ? ? Std.Dev.
?batch? ? (Intercept) 0.000? ?
?Residual? ? ? ? ? ? ?2.789? ?
Number of obs: 24, groups:? batch, 2
Fixed Effects:
(Intercept)??
? ? ? 5.788??

Thanks!
John

 Thanks Jeff for reminding me that the attachment is removed. I put it in my google drive if anyone wants to test the data (https://drive.google.com/file/d/1lgVZVLHeecp9a_sFxEPeg6353O-qXZhM/view?usp=sharing)
I'll try the mixed model mailing list as well.
John
    On Friday, March 4, 2022, 04:56:20 PM PST, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote:

 a) There is a mailing list for that: https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

b) Read the Posting Guide, as most attachment types are removed to avoid propagating worms/viruses. (None seen upon receipt of this email.)

On March 4, 2022 4:41:57 PM PST, array chip via R-help <r-help at r-project.org> wrote:

Dear all, I have this simple dataset to measure the yeild of a crop collected in 2 batches (attached). when I ran a simple inear mixed model using lmer to estimate within-batch and between-batch variability, the between-batch variability is 0. The run showed that data is singular. Does anyone know why the data is singular and what's the reason for 0 variability? is it because the dataset only has 2 batches?

daty<-read.table("datx.txt",sep='\t',header=T,row.names=NULL)
library(lme4)> lmer(yield~1+(1|batch),daty)

boundary (singular) fit: see ?isSingular
Linear mixed model fit by REML ['lmerMod']
Formula: yield ~ 1 + (1 | batch)
  Data: daty
REML criterion at convergence: 115.6358
Random effects:
Groups   Name        Std.Dev.
batch    (Intercept) 0.000
Residual             2.789
Number of obs: 24, groups:  batch, 2
Fixed Effects:
(Intercept)
     5.788

Thanks!
John

--
Sent from my phone. Please excuse my brevity.

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Dear all, I have this simple dataset to measure the yeild of a crop collected in 2 batches (attached). when I ran a simple inear mixed model using lmer to estimate within-batch and between-batch variability, the between-batch variability is 0. The run showed that data is singular. Does anyone know why the data is singular and what's the reason for 0 variability? is it because the dataset only has 2 batches?

daty<-read.table("datx.txt",sep='\t',header=T,row.names=NULL)
library(lme4)> lmer(yield~1+(1|batch),daty)

boundary (singular) fit: see ?isSingular
Linear mixed model fit by REML ['lmerMod']
Formula: yield ~ 1 + (1 | batch)
   Data: daty
REML criterion at convergence: 115.6358
Random effects:
 Groups   Name        Std.Dev.
 batch    (Intercept) 0.000
 Residual             2.789
Number of obs: 24, groups:  batch, 2
Fixed Effects:
(Intercept)
      5.788

Thanks!
John______________________________________________

 Thanks Jeff for reminding me that the attachment is removed. I put it in
my google drive if anyone wants to test the data (
https://drive.google.com/file/d/1lgVZVLHeecp9a_sFxEPeg6353O-qXZhM/view?usp=sharing
)
I'll try the mixed model mailing list as well.
John
    On Friday, March 4, 2022, 04:56:20 PM PST, Jeff Newmiller <
jdnewmil at dcn.davis.ca.us> wrote:

 a) There is a mailing list for that:

summary(aov(yield ~ batch,data=daty))

On Mar 15, 2022, at 12:12 PM, Jixiang Wu <jixiangwu05 at gmail.com> wrote:

There is no difference when running anova or t-test. So you shouldn't
expect positive variance between batches.

On Fri, Mar 4, 2022 at 7:06 PM array chip via R-help <r-help at r-project.org>
wrote:

Thanks Jeff for reminding me that the attachment is removed. I put it in
my google drive if anyone wants to test the data (
https://drive.google.com/file/d/1lgVZVLHeecp9a_sFxEPeg6353O-qXZhM/view?usp=sharing
)
I'll try the mixed model mailing list as well.
John
   On Friday, March 4, 2022, 04:56:20 PM PST, Jeff Newmiller <
jdnewmil at dcn.davis.ca.us> wrote:

a) There is a mailing list for that:

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