data2assayFrame: Check dataframe for pla.fit
In pla: Parallel Line Assays

Description Usage Arguments Details Value Note Author(s) Examples

Check and prepare a dataframe with data for pla, pla.fit, and pla.plots.

data2assayFrame(dataframe,
                dr = 1.5,
                Z = log((1/dr)^(max(Dilution) - Dilution)),
                design = "lsd")

`dataframe`	`dataframe` with the columns `Response`, `Dilution`, `Sample`, and `Replicate` (or `Row` and `Column`).
`dr`	The dilution ratio of the geometric dilution serie with equally spaced dilutions (constant ratio between any adjacent dilutions) on the logarithmic scale.
`Z`	The 'concentration', by default computed as log((1/dr)^{(max(Dilution) - Dilution)}), where `Dilution` is a columns of the argument `dataframe`.
`design`	If "lsd", then `Row` and `Column` has to be columns of the `dataframe`, and a column `Replicate` is copied from `Row`. `Replicate` and `Row` is also used for `'block'` and `'plate'`. `Column` is for "lsd" ("Latin Square Design") used for the 'other' factor. For the designs "crd" and "rbd" `Replicate` has to be a column of the argument `dataframe`.

This function is used internally in pla to check the dataframe that can be given with the data for pla.fit. It can also be used to prepare a dataframe for direct call of pla.fit. Relevant columns are added for pla.fit, and the dataframe is sorted for pla.plots.

A data.frame.

The slope for the potency is computed relative to the added column Z for complete data analysis. Z is NOT used when computing the potency for data without missing values by the method of Ph.Eur.

The dilution ratio dr is also used in the function pheur325 for computing the slope and potency (when the design is complete, i.e. there are no missing values). Thus if a geometric dilution serie not is used, the anova-table and plots might be useful, but not the slope and potency computed by pheur325 and thus by pla.fit.

Sample and Step are transformed to numerics from possible factors (with the orderings of the levels of these factors), and the order of Sample and Step are then reverted. This might give some confusion. data2assayFrame is called from pla, if a data.frame is found as the argument, or as the relevant slot in an argument with this slot. Use as.data.frame on the pla-object to view data data as going into the fitting and plotting functions - for debugging.

Jens Henrik Badsberg

# Example 1:

require(graphics)
Dilution  <- 2 + log(ToothGrowth["dose"]) / log(2)
names(Dilution) <- "Dilution"
Replicate <- rep(1:10, 6)
Data      <- cbind(ToothGrowth, Replicate, Dilution)
dimnames(Data)[[2]] <- c("Response", "Sample", "Dose", "Replicate", "Dilution")
Design    <- "crd"
Frame     <- data2assayFrame(Data, dr = 2, design = Design)
Fits      <- pla.fit(Frame, sampleLabels = c("VC", "OJ"), dr = 2,
                     design = Design, main = "ToothGrowth", show = TRUE)
pla.plots(Frame, design = Design,
          sampleLabels = c("VC", "OJ"), main = "ToothGrowth")

# Example 2:

data(AgarDiffusionAssay)

# Agar   <- read.table("./pla/vignettes/PhEur/data/AntibioticAgarDiffusionAssay.txt",
#                      header = TRUE)
Agar     <- AgarDiffusionAssay
Design   <- "lsd"
select   <- c("Row", "Column", "Sample", "Dilution", "Response")
Frame    <- data2assayFrame(Agar[, select])

fits   <- pla.fit(Frame, design = Design, sampleLabels = c("S", "T"),
                  dr = 1.5, returnPotencyEstimates = TRUE)

## Alternative on object of class 'pla':

plaModel <- plaLSD(Agar)
Fits <- fit(plaModel)