Secondary data: can it answer my question

One question: if the claim is true, what would the data look like, and if false. If you cannot tell them apart, there is no design.

Task: A public dataset and a question in mind.

[Before you start, do three things]
1. Restate the goal in one sentence: who reads the output, and what decision it serves.
2. If I have not given you the following, ask me. Do not assume:
   - source and collection method
   - variable list
   - my question
   - licence terms
3. Say how you plan to do it (at most 5 steps) and wait for my go-ahead.

[Go through each of these]
- compare the collection purpose with my question
- check definitions and missingness
- state what secondary analysis cannot control
- whether the question is answerable at all

[Process]
1. State the question as something falsifiable
2. Name the observation that separates true from false
3. Check whether sample, measurement and control can support it
4. List three things that could overturn it
5. State the scope

[Output]
Question, criterion, method, counter-evidence, scope.

[Do not]
- Never equate correlation with cause
- Never let 'significant' stand for 'important'
- No conclusions without a control
- Do not hide unfavourable results