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whSample helps analysts quickly generate statistical samples from Excel or Comma Separated Value (CSV) files and write them to a new Excel workbook. Users have a choice of Simple Random or Stratified Random samples, and a third choice of having each stratum included in a separate worksheet.
See package vignettes for detailed documentation.
The workhorse function is sampler. A helper function, ssize, estimates the minimum sample size necessary to achieve statistical requirements using a Normal Approximation to the Hypergeometric Distribution. This distribution spans the probabilities of yes/no-type responses without replacement. These parameters are:
ssize(N, ci=0.95, me=0.07, p=0.50) (showing the defaults) only requires the N argument. Used as a standalone, it can be used to explore sample sizes under other conditions. For example, a probe sample may suggest that a 50-50 probability isn’t realistic. A revised sample size can be estimated with the observed success probability (p=0.6, for example).
The sampler function calls ssize to get its sample size estimate. Therefore, it requires the ci, me, and p arguments, which it passes to ssize.
sampler also takes four additional arguments:
The defaults for these additional arguments are backups=5, irisData=F, seed=NULL and keepOrg=F. The default seed will tell sampler to use the current system time in milliseconds. Any number can be used as a seed. Whichever one is used will be listed in the Report output tab. The keep-original option (keepOrg) defaults to FALSE, but could be set to keepOrg=T for smaller populations that wouldn’t exceed Excel’s row limit is 1,048,576 rows.
To override any of these defaults, enter name=value as an argument.
sampler uses a series of menus to guide users through the sampling process.
sampler creates a new Excel workbook with three parts:
a copy of the original (source) data if previously requested,
an Excel spreadsheet with the requested sample, and
a new tab called Report with key reference information:
path and name of the source file
size (in rows) of the source file
sample type (Simple Random Sample, Stratified Random Sample, or Tabbed Stratified Sample)
sampling parameters
sample size
stratification key
number of strata
number of backups requested (this number is applied to every stratum in a stratified sample)
random number seed used, for documentation and reproducibility
date-time stamp of when the sample was generated
stratification information (name, number in the population, proportion of the population, and the number of samples)
You can install whSample from CRAN with:
install.packages("whSample")or get the latest developmental version with:
devtools::install_github("km4ivi/whSample")sampler depends on several external packages to run properly. If you’re running a developmental version, make sure these packages are installed on your computer:
ssize(5000): N=5000, other arguments use defaults
ssize(5000, p=0.60): N=5000, with a 60% expected rate of occurrence
sampler(): Uses all defaults, gets N from the source data.
sampler(backups=2, seed=12345): Overrides specific defaults
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.