pla.fit: Estimation in parallel line models, with listing of results
In pla: Parallel Line Assays

Description Usage Arguments Value Author(s) Examples

The main results are the estimate of potency with confidence interval and the anova table with tests of regression, parallelism and linearity. The anova table can also have test of effect of blocks for Randomized Block Design, and test of row and column for Latin Square Design.

Further the restricted and unrestricted models are fitted without effects of row, columns, and blocks.

The models are fitted by lm, in combination with the function pheur325.

Results are listed directly, or returned in an object. These results can be typeset by LaTex - directly, or by the use of the package xtable.

fit(object, ...) 
pla.fit(data,
        sampleLabels = levels(unlist(data["Sample"])),
        indexOfReference = 1,
        StdName = sampleLabels[indexOfReference],
        design = "blocks",
        dfAdj = 0,
        dr = 2,
        factor = 1,
        alpha = 0.05,
        main = "Parallel Line Model",
        tag = "PLA",
        expectedAnova = NULL,
        expectedPotency = NULL,
        formatTests = "long",
        show = FALSE,
        sink = FALSE,
        Sweave = FALSE,
        printPotencyEstimates = TRUE,
        returnPotencyEstimates = TRUE)

`object`	Object of class pla-class.
`...`	Arguments from `tag` to `printPotencyEstimates` of pla.fit. The other arguments for pla.fit are extracted from the `object` when using `fit(object, ...)`.
`data`	The data.frame with relevant variables - created by data2assayFrame or assayTable2frame.
`main`	A character string giving with the main title for plot (created by pla.plots).
`tag`	A character string giving a part of names of output-files, see e.g. `sink`.
`design`	`crd`, `blocks`, or `latin` for selecting "Completely Randomized Design", "Randomized block design", or "Latin square design".
`dr`	The dilution ratio of the equally spaced dilutions.
`dfAdj`	The needed adjustment of the number of degrees of freedom, if data are corrected for blocks, rows or columns before applying the model of the completely randomized design on block designs, or if values are imputed.
`sampleLabels`	A vector of character strings giving the labels of the `samples`. If `data["Sample"]` has one of these values, then these rows are used. These labels are also used for labels of the returned values.
`indexOfReference`	Index of the reference among the samples given by `sampleLabels`.
`StdName`	A character string identifying the reference in the columns `Sample` of the input data `data`. If `data["Sample"]` has this value, then these rows are from the 'reference'.
`formatTests`	A vector of character string, `"long"`, `"short"`, `"both"`, `"none"` to select format for results of validity tests.
`show`	A logical or subset of "head", "anova", "tests", "regressions", "ratios", "pheur", "rsquare", "slope", "logpotency", "potency"). If `TRUE` then all the results are reported.
`sink`	Output is diverted to `paste(tag, "-Result.txt", sep = "")` if this boolean is `TRUE`.
`alpha`	A numeric (vector), the level of significance for test of validity, default `0.05`. `alpha` can be a named vector with the levels of significance for the tests of `Regression`, `Linearity`, `Parallelism`, and the complementary probability `alpha` of the `Confidence` interval of the potency. If more than one probability is supplied for one test of validity, then `"Unknown"` is reported for tests with probability between the supplied values, with counts of limits exceedded.
`Sweave`	If `TRUE` then code is inserted in the output listing for page breaking in LaTeX.
`factor`	A numeric (vector) to multiply on the estimated potency.
`expectedAnova`	A numeric matrix with the expected ANOVA table.
`expectedPotency`	A numeric matrix with the expected potency.
`printPotencyEstimates`	If `TRUE` then computed potency values are listed (for Sweave).
`returnPotencyEstimates`	If `TRUE` then computed potency values are returned.

No values returned.

Jens Henrik Badsberg

data(Turbidimetric); Data <- Turbidimetric

Design <- "blocks"
Data   <- readAssayTable(paste(system.file(package = "pla"),
                           "vignettes/PhEur/data/AntibioticTurbidimetric.txt",
                           sep = "/"))
Frame  <- as.data.frame(Data, dr = 1.5)

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

## Alternative on object of class 'pla':

plaModel <- plaRBD(Data)
Fits <- fit(plaModel)