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 -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... Name: datx.txt URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20220305/296d04e5/attachment.txt>
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.
I think the best analysis of this data is: library(lattice) dotplot(yield ~ batch, daty) bwplot(yield ~ batch, daty) There is no detectable difference between batches. But, if you insist, try removing the overall intercept. m1 <- lmer(yield~0+(1|batch),daty) coef(m1) summary(m1) VarCorr(m1) On Fri, Mar 4, 2022 at 6:44 PM 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______________________________________________ > 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.-- Kevin Wright