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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Do you really think a variance from a sample size of 2 makes any sense? Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Fri, Mar 4, 2022 at 5:06 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: 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. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.
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: > 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. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]