Creating Rich Results

In this section, we are going to transform our raw text output into a nice, professional, APA-formatted table.

1. Upgrading the Results Definition (`.r.yaml`)

If you open jamovi/ttest.r.yaml right now, you’ll see the boilerplate text element that jmvtools automatically generated for us earlier:

items:
    - name:  text
      title: Independent Samples T-Test
      type:  Preformatted

type: Preformatted: This is a simple container for raw text output. We’ve been using this so far with setContent() to dump our raw R findings.

To provide rich results, we are going to add a new structured Table container. Modify your ttest.r.yaml to add the ttest table underneath the existing text item:

---
name:  ttest
title: Independent Samples T-Test
jrs:   '1.1' # jamovi results spec

items:
    - name:  text
      title: Independent Samples T-Test
      type:  Preformatted
    - name:  ttest
      title: Independent Samples T-Test
      type: Table
      rows:  1
      columns:
        - name: var
          title: ''
          type: text
        - name: t
          type: number
        - name: df
          type: integer
        - name: p
          type: number
          format: zto,pvalue
...

type: Table: Reserves space for a structured table.
format: zto,pvalue: zto (zero-to-one) is for values that fall in the 0 -> 1 range, and pvalue is for p-values. These format codes instruct jamovi how to format these values (i.e. if the value is very small, it might be rendered < .001).

If you reinstall your module right now (jmvtools::install()), jamovi reads your results definition and generates the new table UI below your existing text output. However, because our R code isn’t filling the table yet, it will be completely blank:

2. Populating the Table

Now we need to update our construction crew in R/ttest.b.R to extract values from the R t-test object and “pour” them into the new table.

Update your .run() function to match the complete implementation below. Notice how we are leaving the old self$results$text$setContent(results) line exactly where it is for now:

Note

Handling R Objects

R functions return different types of objects (S3, S4, or Lists), and extracting the values you need often takes a little trial and error. Here are the most useful tools for introspecting an object in your R console:

Function	What it tells you
`class(results)`	The object type (e.g. `htest`, `lm`, `list`)
`names(results)`	The named fields you can access with `$`
`str(results)`	A compact overview of the full structure and types
`results$statistic`	Access a named field directly with `$`

A typical workflow: run your analysis interactively in the R console, call str(results) to see what’s inside, then use $ or [[ to drill down to the exact value you need.

.run=function() {
    # 1. Input Check: Stop quietly if inputs are missing
    if (length(self$options$dep) == 0 || length(self$options$group) == 0) {
        return()
    }

    # 2. Construct the formula (e.g., "len ~ supp")
    formula <- jmvcore::constructFormula(self$options$dep, self$options$group)
    formula <- as.formula(formula)

    # 3. Run the analysis (using the stats namespace)
    results <- stats::t.test(formula, self$data, var.equal=self$options$varEq)

    # 4. Populate the results panel
    self$results$text$setContent(results)

    # 5. Access the table object
    table <- self$results$ttest

    # 6. Fill in the row
    table$setRow(rowNo=1, values=list(
        var = self$options$dep,
        t   = results$statistic,
        df  = results$parameter,
        p   = results$p.value
    ))
}

Now, reinstall your module with jmvtools::install(). Thanks to the new logic, your beautiful, formatted table is seamlessly populated in jamovi right below your raw text:

final table

3. Cleaning Up

We successfully built our rich table! Now we don’t need that ugly raw text output cluttering the screen anymore.

As a final cleanup step:

Go back to ttest.r.yaml and delete the entire text item.
Open ttest.b.R and delete the obsolete self$results$text$setContent(results) line.

If you reinstall your module one last time, you’ll have a pristine, professional results panel: