Input Checks

Your analysis now works — but try removing the variables from the inputs in jamovi. You’ll see a confusing error message in the results panel. In this section, we’ll fix that by adding an Input Check.

1. The Problem

By default, jamovi runs your analysis as soon as it’s opened. If the user hasn’t provided the required variables yet, R will throw an error while trying to construct the formula.

Try removing len and supp from your analysis in jamovi. You’ll see a generic error message in the results panel:

This isn’t technically a bug — it just means the analysis ran before the user was ready.

2. The Solution: Exit Early

We add an Input Check (also known as an Early Return or Guard Clause) at the very top of our .run() function. This tells R: “If the required options are empty, stop here quietly — don’t show an error.”

Modify your R/ttest.b.R to add the check:

ttestClass <- R6::R6Class("ttestClass",
    inherit = ttestBase,
    private = list(
        .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
            formula <- jmvcore::constructFormula(self$options$dep, self$options$group)
            formula <- as.formula(formula)

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

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

Now reinstall with jmvtools::install(). The results panel will stay clean until both variables are assigned, providing a much smoother user experience.

Next Step: Now that your analysis is stable, let’s understand the model behind jamovi’s results system before we build something more powerful: The jamovi Results Model.