rMatrix provides a correlation matrix with confidence intervals and a p-value adjusted for multiple testing.
rMatrix(dat, x, y=NULL, conf.level = .95, correction = "fdr", digits = 2, pValueDigits=3, colspace=2, rowspace=0, colNames ="numbers", output="R", env.LaTeX = 'tabular', pboxWidthMultiplier = 1)
- A dataframe containing the relevant variables.
- Vector of 1+ variable names.
- Vector of 1+ variable names; if this is left empty, a symmetric matrix is created; if this is filled, the matrix will have the x variables defining the rows and the y variables defining the columns.
- The confidence of the confidence intervals.
- Correction for multiple testing: an element out of the vector c("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none"). NOTE: the p-values are corrected for multiple testing; The confidence intervals are not (yet :-)).
- With what precision do you want the results to print.
- Determines the number of digits to use when displaying p values. P-values that are too small will be shown as p<.001 or p<.00001 etc.
- Number of spaces between columns (only for R output, ignored for LaTeX output)
- Number of rows between table rows (note: one table row is 2 rows; only for R output, ignored for LaTeX output).
- colNames can be "numbers" or "names". "Names" cause variables names to be printed in the heading; "numbers" causes the rows to become numbered and the numbers to be printed in the heading.
- Can be "R" or "LaTeX"; if output is set to "LaTeX", the result is a LaTeX table (e.g. for use in knitr).
- For LaTeX output, the environment can be set with env.LaTeX.
- When using LaTeX, pboxWidthMultiplier can be used to make the cells narrower or wider (1 works for anything up until 4 or 5 digits).
rMatrix provides a symmetric or asymmetric matrix of correlations their confidence intervals, and p-values. The p-values can be corrected for multiple testing.
An object with the input and several output variables. Most notably a number of matrices:
rMatrix(mtcars, x=c('disp', 'hp', 'drat'))