Part 3 – Reproduction and exploration
Part 3 has two hands-on tasks, the reproduction and a first exploration of the menu of alternatives, with the talk that connects them in between.
| Work through | What you do | Timing |
|---|---|---|
| Slides, Part 3 | The three Multi100 instructions read verbatim, what each of them assumes, the columns of the panel, and the aim of the reproduction you are about to run. | 15 minutes |
| Your working script in the workspace, or Browser lab Task 3 | Fit mcosmo ~ unemp_c with country and year fixed effects, which should give t = −3.804 (df = 233, N = 270), the value recorded by Multi100 for analyst C6HJR. Everyone types their t without sending it and sends it when the facilitator says go, so that the identical values appear at the same moment. |
22 minutes |
| Specification menu and slides | First, why everyone in the class got the same t while the five published analysts, each writing their own code, did not. Then the axes you choose from, one option each: frame set, scoring rule, predictor, copredictor, sample, weight and estimator at Level 1, the measurement choices at Level 2, and the form, family and standard errors at Level 3. Last, what Task 2 of Multi100 left open, including the unit of analysis, and the claim-alignment convention that puts every result on one scale. | 20 minutes |
| Slides, the methodological tutorial | Optional depth: what each axis actually does to an estimate. The outcome, claim alignment and estimator slides are the core of it. | 13 minutes |
| Task 4 in the workspace or on the Browser lab, then Multiverse | Call try_spec() three or four times, changing one argument at a time, print them side by side with my_experiments(), then pick the one you would defend and send it with submit_exploration(). Your dot is drawn on the chart as an open circle. |
20 minutes |
By the end of the part you have reproduced t = −3.804 yourself, tried three or four alternatives one argument at a time, and put an exploratory dot on the class chart.