Module 02 Activity

Scenario

A dataset has arrived for a comparison. Establish what one row is and whether the table can support the test at all.

What you build

An analysis table with a stated grain, declared factor levels and a passing check list.

Steps

1. Write down the outcome, the predictor, any grouping, the unit of analysis and the time window before touching the data.
2. Classify every variable — numeric, categorical, ordinal, count, rate, binary — and note which tests each admits.
3. Count missing values by group. Report whether missingness is balanced, and state what complete-case analysis assumes.
4. Count distinct units alongside rows. If units repeat, aggregate to one row per unit before testing.
5. Convert grouping variables to factors and set the reference to the meaningful baseline with relevel().
6. Run the six-check list and treat every failure as a question for the data owner.

Evidence to hand in

• The five decisions, written before the analysis.
• The variable classification.
• The missingness table by group.
• Rows versus distinct units, and any aggregation you did.
• The declared factor levels and reference.
• The check-list results, with what each failure led to.

Review checklist

• The unit of analysis is stated and the table's grain matches it.
• Missingness is counted by group and its balance reported.
• Repeated measurements are aggregated, or the dependence is addressed.
• Every grouping variable is a factor with a deliberately set reference.
• No failed check was silently relaxed.

Mark complete