checkData function

Check Random Model for Given Dataset.

Check Random Model for Given Dataset.

This function is intended to check a variance component analysis either before or after performing it. This is particularily important for less experienced users who my not exactly know where error messages come from. External software using functions anovaVCA

or remlVCA also via function fitVCA may also benefit from more user-friendly error messages.

checkData(form, Data)

Arguments

  • form: (formula) describing the model to be analyzed
  • Data: (data.frame) with all variables used in 'form'

Returns

(list) of length equal to the number of terms in 'form' each element being a list of messages with identified, potential problems.

Examples

## Not run: data(dataEP05A2_1) dat0 <- dataEP05A2_1[1:16,] # everything should be ok checkData(y~day/run, dat0) # data identical response for all obs dat1 <- dat0 dat1$y <- dat1[1,"y"] remlVCA(y~day/run, dat1) checkData(y~day/run, dat1) # now factor-levels have identical values dat2 <- dat0 dat2$y <- dat2$y[rep(seq(1,7,2), rep(2,4))] checkData(y~day/run, dat2) remlVCA(y~day/run, dat2, quiet=TRUE) # indistinguishable terms are also problematic dat3 <- data.frame( y=rnorm(8,10), day=paste("day",rep(c(1,2),c(4,4))), run=rep(c(2,1), c(4,4))) checkData(y~day/run, dat3) anovaVCA(y~day/run, dat3) # no replicates, thus, no error variability dat4 <- dat0[seq(1,15,2),] dat4$day <- factor(dat4$day) dat4$run <- factor(dat4$run) checkData(y~day/run, dat4) remlVCA(y~day/run, dat4) ## End(Not run)

Author(s)

Andre Schuetzenmeister andre.schuetzenmeister@roche.com

  • Maintainer: Andre Schuetzenmeister
  • License: GPL (>= 3)
  • Last published: 2024-03-07

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