orderData | R Documentation |
Functions attempts to standardize input data for linear mixed model analyses to overcome the problem that analysis results sometimes depend on ordering of the data and definition of factor-levels.
orderData(Data, trms, order.data = TRUE, exclude.numeric = TRUE, quiet = FALSE)
Data |
(data.frame) with input data intented to put into standard-order |
trms |
(formula, terms) object speciying a model to be fitted to |
order.data |
(logical) TRUE = variables will be increasingly ordered, FALSE = order of the variables remains as is |
exclude.numeric |
(logical) TRUE = numeric variables will not be included in the reordering, which is required whenever this variable serves as covariate in a LMM, FALSE = numeric variables will also be converted to factors, useful in VCA-analysis, where all variables are interpreted as class-variables |
quiet |
(logical) TRUE = omits any (potentially) informative output regarding re-ordering and type-casting of variables |
Andre Schuetzenmeister andre.schuetzenmeister@roche.com
## Not run: # random ordering data(dataEP05A2_1) dat <- dataEP05A2_1 levels(dat$day) <- sample(levels(dat$day)) # this has direct impact e.g. on order of estimated effects fit <- anovaVCA(y~day/run, dat, order.data=FALSE) ranef(fit) # to guarantee consistent analysis results # independent of the any data orderings option # 'order.data' is per default set to TRUE: fit <- anovaVCA(y~day/run, dat) ranef(fit) # which is identical to: fit2 <- anovaVCA(y~day/run, orderData(dat, y~day/run), order.data=FALSE) ranef(fit2) ## End(Not run)
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