Description
Harrell Miscellaneous.
Description
Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, simulation, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, recoding variables, caching, simplified parallel computing, encrypting and decrypting data using a safe workflow, general moving window statistical estimation, and assistance in interpreting principal component analysis.
README.md
Hmisc
Harrell Miscellaneous
Current Goals
- Continue to refine the summaryX class of functions that replace tables with graphics
- See also bpplotM and tabulr
- See https://hbiostat.org/R/Hmisc/summaryFuns.pdf
Web Sites
- Overall: https://hbiostat.org/R/Hmisc
- CRAN: http://cran.r-project.org/web/packages/Hmisc
- Changelog: https://github.com/harrelfe/Hmisc/commits/master
To Do
- Consider using the haven package for importing SAS, Stata, and SPSS files; haven stores labels as the label attribute of each variable as does Hmisc; it converts date and time variables automatically and allows one to specify a format catalog along with the primary dataset
- See if the readstata13 package has advantages over the foreign package for Stata file import
- Consider creating xl.get using the readxl package to read .xls and .xlsx Excel files
- In impute.transcan, sense if a variable in data is not a factor whereas it was treated as a factor during aregImpute; it should be converted to factor before the line v[sub] <- ... levels(as.integer...)) is run.