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pla (version 0.1)

pla-package: Parallel Line Assays

Description

Parallel Line Models:

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.

Arguments

Details

ll{ Package: pla Type: Package Version: 0.1 Date: 2015-08-18 License: GPL (>= 2) }

Contents:

  • readAssayTable: Reads (.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 methodsas.data.frame,as.array, andas.table. % Many examples of input data are found in the folder % \code{.../pla/vignettes/'Source'/data/}.
  • pla: Functions for defining and creating parallel line assay models. Imputation of missing values is performed, as an option.
  • pla.fitorfiton pla-model: Estimation in parallel line models, with listing of results.
    • pheur325: Estimation of potency and confidence limits as described at page 480 in the Ph.Eur.
  • pla.plotsorploton pla-model: Make plots for parallel line models.
    • plotSamples: One scatter plot for parallel line models.
    • jitterSteps: Compute a perturbed version of the concentration-variable.

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. 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".

References

Ph.Eur.: Chapter 5.3. Statistical analysis. In EUROPEAN PHARMACOPOEIA 5.0, 2004; 475-504.

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.