Completely Randomized Design, Randomized Block Design, and Latin Squares Design.
Balanced data are fitted as described in the Ph.Eur.
In the presence of missing values complete data analysis can be performed (with computation of Fieller's confidence intervals for the estimated potency), or imputation of values can be applied.
The package contains a script such that a pdf-document with a
report of an analysis of an assay can be produced from an input file
with data of the assay just by entering the name of the input-file.
Here no knowledge of R is needed by the user.
This tool requires R and Tex
(e.g. MikTex) to be installed.
The .BAT- and .csh-files for this is found in
.../pla/scripts/ of your installed pla package.
You can of course modify the "skeleton"
(.../pla/scripts/Skeleton/Skeleton-xtable.Rnw)
Sweave program of this script.
You should not (only) place your data in .../pla/scripts/data,
but copy the content of the directory .../pla/scripts/ to some
place not effected by updates of R and the pla-package.
| Package: |
| pla |
| Type: |
| Package |
| Version: |
| 0.2 |
| Date: |
| 2015-09-09 |
| License: |
| GPL (>= 2) |
Contents:
.txt) files with
responses of assays, entered as matrices with rows of measurements
by columns of factors and variables, or entered as tables (arrays)
of responses. The result has methods as.data.frame,
as.array, and as.table.
Many examples of input data are found in the folder
.../pla/vignettes/'Source'/data/.
The two main functions are pla.fit and pla.plots, which expects data in the format as returned by assayTable2frame or data2assayFrame. But the function readAssayTable is also very useful.
One way to understand (and to reproduce) the structure of the expected
input of pla.fit and pla.plots is to look into
data2assayFrame and AgarDiffusionAssay.
The column names Response, Dilution, Sample,
Replicate, Row, and Column of the input for
data2assayFrame cannot be changed.
Row and Column are used for "Latin squares".
Replicate is used for "blocks" and completely random
designs.
pheur325 is designed to be called from pla.fit, and plotSamples is designed to be called from pla.plots.
The input dataframe for pla.plots and pla.fit should be
ordered by Sample and "DilutionStep".
The output listing is designed for "R CMD Sweave" and "pdflatex".
Acknowledgment: Thanks to CombiStats for permitting the presentation of the data of CombiStats in this package. The statistical analyses of this data are also performed by the CombiStats program, and the results can be found on http://combistats.edqm.eu/.
Coward, Katrine Hope, Kassner, Elsie Woodward (1941): A Comparison between Interlitter and Intralitter variation in rats with respect to the healing of rachitic bones by vitamin D. Pharmaceutical Society, London. Fieller, E.C.: The biological standardization of insulin. Supplement to the Journal of the Royal Statistical Society. 1940; Vol. VII., No. 1. Bliss, C.I. (1952): The Statistics of Bioassay - with special reference to the vitamin. Academic Press, New York.
Arthur Linder, Genova, Switzerland (1964): Statistics of Bioassays, Notes on lectures held during the spring semester (1964) at the Statistics Department, University of North Carolina, Chapel Hill, N. C.
Finney, David J. (1978): Statistical Method in Biological Assay. Charles Griffin & Company Ltd. Third Edition.
data(Corticotrophin); Data <- Corticotrophin
Design <- "crd"
Data <- readAssayTable(paste(system.file(package = "pla"),
"vignettes/PhEur/data/Corticotrophin.txt",
sep = "/"))
Frame <- as.data.frame(Data)
fits <- pla.fit(Frame, design = Design, sampleLabels = c("S", "T", "U"),
dr = 4, returnPotencyEstimates = TRUE)
plots <- pla.plots(Frame, design = Design, sampleLabels = c("S", "T", "U"),
colTst = c("blue", "red"), showRho = FALSE,
main = "PhEur: Corticotrophin; Subcutaneous Injection In Rats",
tests = fits@tests,)
## Alternative on object of class 'pla':
plaModel <- plaCRD(Data,
assayTitle = "PhEur: Corticotrophin; Subcutaneous Injection In Rats")
Fits <- fit(plaModel)
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