scaleInspection is a function to generate a PDF with information to diagnose and inspect scales (aggregate measures); makeScales actually generates the scales; and meanConfInt and sdConfInt provide confidence intervals for means and standard deviations.
scaleInspection(dat, items = NULL,
docTitle = "Scale inspection", docAuthor = "Author",
pdfLaTexPath, rnwPath=getwd(),
filename = "scaleInspection", convertFactors=TRUE,
scaleReliability.ci=FALSE, conf.level=.95, digits=2,
rMatrixColsLandscape = 6,
pboxWidthMultiplier = 1,
scatterPlotBaseSize = 4,
pageMargins=15, show=FALSE,
pval=TRUE)
makeScales(dat, scales, append=TRUE)
meanConfInt(vector=NULL, mean=NULL, sd=NULL, n=NULL, se=NULL, conf.level=.95)
sdConfInt(vector=NULL, sd=NULL, n=NULL, conf.level=.95)Dataframe containing the items of the relevant scale
Either a character vector with the itemnames, or, if the items are organised in scales, a list of character vectors with the items in each scale.
A list of character vectors with the items in each scale, where each vectors' name is the name of the scale.
Title to use when generating the PDF.
Author(s) to include when generating the PDF.
The path to PdfLaTex. This file is part of a LaTeX installation that creates a pdf out of a .tex file.
In Windows, you can download (portable) MikTex from http://miktex.org/portable. You then decide yourself where to install MikTex; pdflatex will end up in a subfolder 'miktex\bin', so if you installed MikTex in, for example, 'C:\Program Files\MikTex', the total path becomes 'C:\Program Files\MikTex\miktex\bin'. Note that R uses slashes instead of backslashes to separate folders, so in this example, pdfLaTexPath should be 'C:/Program Files/MikTex/miktex/bin'
In MacOS, you can install MacTex from http://tug.org/mactex/ By default, pdflatex ends up in folder '/user/texbin', which is what pdfLaTexPath should be in that default case.
In Ubuntu, you can install TexLive base by using your package manager to install texlive-latex-base, or using the terminal: 'sudo apt-get install texlive-latex-base' In ubuntu, by default pdflatex ends un in folder '/usr/bin', which is what pdfLaTexPath should be in that default case.
The path where the temporary files and the resulting PDF should be stored.
The filename to use to save the pdf.
Whether to convert factors to numeric vectors for the analysis.
TRUE or FALSE: whether to compute confidence intervals for Cronbach's Alpha and Omega (uses bootstrapping function in MBESS, takes a while).
Confidence of confidence intervals (for reliability estimates (if requested with scaleReliability.ci), meand, and sd, for respectively scaleInspection, meanConfInt and sdConfInt).
The number of digits to use in the tables.
At how many columns (or rather, variables) or more should rMatrices be printed landscape?
Used for print.rMatrix; used to tweak the width of columns in the correlation matrix.
Size of one scatterplot in the scattermatrix in centimeters. If the total scattermatrix becomes larger than 18 cm, it's scaled down to 18 cm.
Margins of the page in millimeters.
Whether to show the results (or only write them to the PDF).
Whether to print p-values as p-values in correlation matrix.
Whether to return the dataframe including the new variables
(TRUE), or a dataframe with only those new
variables (FALSE).
Numeric vector to use when computing confidence intervals.
Mean to use when computing confidence intervals (when no vector is provided).
Standard deviaton to use when computing confidence intervals (when no vector is provided).
Number of datapoints to base confidence intervals on.
Standard errorto use when computing confidence intervals (when no standard deviation or vector is provided).
scaleInspection returns nothing; it just generates a PDF.
makeScales returns the provided dataframe, now including the new scale variables.
meanConfInt and sdConfInt return an object, with in its 'output' list, the confidence interval for a mean or standard deviation.
scaleInspection generates a PDF with useful diagnostics to assess a scale; those from scaleDiagnosis and an rMatrix.
makeScales generates the scales and stores them in the dataframe.
meanConfInt and sdConfInt just compute and return a confidence interval for a mean or standard deviation.
# NOT RUN {
# }
# NOT RUN {
scaleInspection(mtcars, items=c('disp', 'hp', 'drat'), pdfLaTexPath="valid/path/here");
# }
# NOT RUN {
newDataframe <- makeScales(mtcars, list(senselessScale = c('disp', 'hp', 'drat')));
sdConfInt(sd=4, n=30);
meanConfInt(mean=5, sd=4, n=30)
# }
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