r i = {{i}}
r vars[i]
lc <- ck.abd(dfr, vars[i], geno, rep) # Remove checks without data or with only one datum if (lc$nck.0 > 0 | lc$nck.1 > 0) { tmp <- dfr[!(dfr[, geno] %in% c(lc$ck.0, lc$ck.1)), ] } else { tmp <- dfr } # Remove missing values for DAU.test tmp <- tmp[!is.na(tmp[, vars[i]]), ] # Fit model y <- tmp[, vars[i]] model <- agricolae::DAU.test(tmp[, rep], tmp[, geno], y)
r if(lc$nmis == 0 & lc$nmis.ck == 0) {"For this variable there are no missing values."}
r if(lc$nmis == 1) {"There is one genotype with missing value. This genotype has been removed."}
r if(lc$nmis > 1) paste("There are", lc$nmis, "genotypes with missing values. These genotypes have been removed.")
r if(lc$nmis > 0) paste("Therefore, there are", lc$ng - lc$nmis, "genotypes included in the analysis.")
r if(lc$nck.0 == 1) paste0("There is one check without data: ", lc$ck.0, ". This check has been removed.")
r if(lc$nck.0 > 1) paste0("There are ", lc$nck.0, " checks without data: ")
if(lc$nck.0 > 1) lc$ck.0
r if(lc$nck.0 > 1) {"These checks have been removed."}
r if(lc$nck.1 == 1) paste0("There is one check with data in only one block: ", lc$ck.1, ". Checks need at least two replications so this check has been removed.")
r if(lc$nck.1 > 1) paste0("There are ", lc$nck.1, " checks with data in only one block: ")
if(lc$nck.1 > 1) lc$ck.1
r if(lc$nck.1 > 1) {"Checks need at least two replications so these checks have been removed."}
model$means
model$statistics
model$groups
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