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1.
How will your primary outcome be assessed?
Linear regression? Logistic regression? What are your covariates and confounders? How to account for clustered randomization? Random effect model? Fixed effect model? What software will you use?
2.
4.
Check for missing and implausible data.
Examine using a data collector. Is the data quality heterogeneous? Are there ceiling or floor effects? Look for "epidemiological consistencies."
3.
5.
Data quality checks.
Distribution of scores, inter-rater agreement, test-retest reliability, internal reliability, comparison with norms, correlation with expected variables, differences between testers.
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