Reference
Below are the jstats functions and datasets, grouped by what they do. First, two quick notes on getting help.
Getting help within RStudio
Every function has a built-in help page. The quick way to open one in RStudio is to click the function’s name — in your script or the console — and press F1 (or Fn+F1 on most Macs). In any R setup you can also type ? followed by the name — for example, ?jfreq. Either way you get the description, the options, and worked examples.
What this site adds
The function and dataset names below link to those same help pages online — and those pages rebuild themselves automatically from the package. Whenever the package changes or a new function is added, they regenerate from its built-in documentation and the examples are re-run, so the documentation and the code never drift apart: what you see is always current. The payoff is that every example shows the real output the call produces, not output typed in by hand — so you can copy one and trust it matches what you’ll get.
Over time this section will grow into a task-indexed reference — a place to look up how to do a specific thing while you work, organized by what you want to do rather than by function name. For now, it’s a grouped map of what’s available, with each name linking to its full help page.
Describe and explore
Tests and models
Scales and reliability
Prepare and manage your data
jrecode— recode a variable using an explicit value mapping, with optional labels.jrelabel— add or change a variable’s variable- and value-labels.jdeclare_udm— declare user-defined missing values (values that should count as missing, such as a “Refused” code) without overwriting your data.jsubset— set a case-selection filter so functions run on a chosen subset of cases.jcomplete— set a listwise complete-case filter so a run of analyses share a matching N.jcopy— copy a data frame, carrying any of its variable settings along with it.
Open, save, and convert files
jload— open a data file (from commercial statistical software, Excel, or CSV) in one command, bringing its value labels, variable labels, and missing-value codes along automatically.jsave— save a data frame back out to a file.jconvert— convert missing-value declarations between the conventions different programs use.jdata_dir— show the folder jstats reads your data files from.
Set up your session
juse— set (or display) the default dataset, so you don’t have to name it in every call.joptions— set or display session-level options, such as the data folder.joutput— set how much detail jstats prints (the output verbosity level).jupdate— update jstats to the latest version (one command; restart R afterward to load it).
Plots
jplot— plot a jstats result, or draw a quick plot of variables straight from a dataset.
Fine-tuning: tell jstats how to treat a variable
Most users will not need these. jstats works out what kind each variable is on its own; these let you override that when you want a particular variable handled a particular way.
Datasets
jstats ships with two practice datasets, both available the moment the package loads:
community— a clean 100-respondent community survey (income, education, age, a wellbeing score, several yes/no items, a region, and a five-item attitude scale). The package’s default example data; it’s what every function’s help examples use.clinic— a deliberately messy 70-client mental-health and wellbeing sample, the companion for practicing data cleaning: it carries undeclared missing-value codes, stripped labels, and imperfect scale items to work through.
On the way
A few capabilities are planned for future versions — among them regression for count outcomes (Poisson and negative-binomial models) and exporting formatted, APA-style results to Word. The function set above is what ships today.