Timeline variables, randomization, scoring, and summaries
Bartosz Maćkiewicz
Build one reusable trial, run it over many items, and show that the resulting rows match the design.
Artifact: a small randomized Stroop pilot with accurate summaries.
Open last meeting’s export and verify your answers.
Yes, a fixation produces a row. A timeout stores null response and null RT. Refreshing loses unsaved in-memory results.
Describe the design in an item table; define the procedure once.
A new item should not require copying the whole experiment.
Open the lab in its own tab · Predict → edit → run → inspect · The preview captures response keys.
Use all four arithmetic items in
materials/live-starter/. Randomize their order.
F = even result; J = odd result.
Verify four distinct item IDs and correct visible arithmetic.
Audit counts before inspecting response times.
A list with three congruent items and one incongruent item remains 3:1 after shuffling.
For every task row, store:
Keep instructions and fixation easy to filter out.
Answer one parity item correctly, one incorrectly, and let one time out.
Reconstruct the expected key from the arithmetic itself. Compare it with the saved fields.
A saved answer key cannot validate itself.
Accuracy = correct decisions / all task decisions.
Mean RT = mean of correct responses with finite RT.
For the eight-row teaching dataset: 50% accuracy, 800 ms mean correct RT.
Add the supplied summary to the timeline. Its stimulus is a function so it reads the completed data.
Run once normally and once with no correct answers. Explain the displayed accuracy, omissions, and RT.
Open the lab in its own tab · Predict → edit → run → inspect · The preview captures response keys.
Use 98_Resources/data/synthetic-pilot.csv.
Eight task trials, four correct, two omissions. Correct RTs: 500, 700, 900, 1100 ms.
Calculate accuracy and mean correct RT before checking the key.
Respond to the ink, ignoring the word.
F = red; G = blue; H = green; J = black.
Congruent: word and ink match. Incongruent: word and ink differ.
Use the arrow alternative if color discrimination is unsuitable.
Extend to 16 balanced items in Assignment 2.
A difference between two tiny classroom averages is not sufficient evidence for a psychological effect.
Item confounds, errors, practice, devices, and sampling matter. Do not choose exclusions to make the expected pattern appear.
Explain when to use timelineVariable versus
evaluateTimelineVariable.
Which rows enter accuracy? Which enter RT? What is displayed when no correct response exists?
Before Meeting 3: Assignment 2, a practice/test flow sketch, and the short local JATOS setup guide. Bring a working task.