[R-sig-ME] A consultation about lmer
Thierry Onkelinx
th|erry@onke||nx @end|ng |rom |nbo@be
Tue Dec 24 11:24:47 CET 2019
Dear anonymous,
The assumption of normality is on the residuals, not on the observations.
The assumption holds reasonably for the sleepstudy, except for a few
outliers.
library(lme4)
fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
qqnorm(residuals(fm1))
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx using inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be
///////////////////////////////////////////////////////////////////////////////////////////
To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey
///////////////////////////////////////////////////////////////////////////////////////////
<https://www.inbo.be>
Op ma 23 dec. 2019 om 17:36 schreef 何如梦 <18754808835 using 163.com>:
> I have some confusion about the use of lmer. As I learned the data
> should be normal distributed when use liner mixed model. I tested the
> exmple data (Reaction$sleepstudy) by using shapiro.test. The result shows
> that it was not normal distributed. So I have some confusion about the
> requirment of data distribution in function lmer and glmmer.
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models using r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
[[alternative HTML version deleted]]
More information about the R-sig-mixed-models
mailing list