Dear members, I am trying to reproduce analyse an alpha lattice design (an unbalanced design) in `lme4`. https://cran.r-project.org/web/packages/agridat/agridat.pdf#page.184 library(agridat) library(lme4) The model can be fitted in lme4 # genotypes - fixed model <- lmer(yield ~ 0 + gen + rep + (1|rep:block), dat) # genotypes - random model <- lmer(yield ~ 0 + (1|gen) + rep + (1|rep:block), dat) However further calculations seem to required `asreml`. library(asreml) m3 <- asreml(yield ~ 1 + rep, data=dat, random=~ gen + rep:block) sg2 <- summary(m3)$varcomp[1,'component'] vblup <- predict(m3, classify="gen")$pred$avsed ^ 2 m3 <- asreml(yield ~ 1 + gen + rep, data=dat, random = ~ rep:block) vblue <- predict(m3, classify="gen")$pred$avsed ^ 2 sg2 / (sg2 + vblue/2) 1-(vblup / 2 / sg2) Here `avsed` is the "mean variance of difference of adjusted means" (BLUP or BLUE). Is it possible to replicate the last part also in `lme4`? `avsed` can be computed from the "variance-covariance matrix of adjusted means" for genotypes. ( https://static-content.springer.com/esm/art%3A10.1186%2F1471-2164-14-860/MediaObjects/12864_2013_5591_MOESM1_ESM.doc). How to get that matrix from lme4? Warm Regards,
J.Aravind Division of Germplasm Conservation, ICAR-National Bureau of Plant Genetic Resources, New Delhi - 110 012 <aravindj at nbpgr.ernet.in> [[alternative HTML version deleted]]