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2. New Data Cleaning Structure
To improve modularity and maintainability, we will split the current stage_1_data_cleaning.R into four separate scripts:
Setting Reference Levels – Defines reference levels for categorical variables.
Quality Assurance – Applies data validation checks and flags potential issues.
Inclusion Criteria – Implements study-specific inclusion and exclusion rules.
Main Data Cleaning Script – Calls the above functions and outputs the final cleaned datasets.
No intermediate outputs (e.g., consort, consort_midpoint6, output.rds) will be generated after the Quality Assurance step.
Final cleaned datasets will be produced for each cohort (prevax, vax, unvax).
The text was updated successfully, but these errors were encountered:
Decisions from the Meeting on 28th Jan 2025
1. Removal of Vaccination Product Variables
Missing Variables: No vax_cat_product_* variables were found in either the old or new repositories.
Action: The following code can be removed, as it is no longer needed:
https://github.com/opensafely/post-covid-mentalhealth/blob/ddb50bd8fc9e4e1a9855dc9f9a03991487c908aa/analysis/stage1_data_cleaning.R#L136-L142
2. New Data Cleaning Structure
To improve modularity and maintainability, we will split the current stage_1_data_cleaning.R into four separate scripts:
Setting Reference Levels – Defines reference levels for categorical variables.
Quality Assurance – Applies data validation checks and flags potential issues.
Inclusion Criteria – Implements study-specific inclusion and exclusion rules.
Main Data Cleaning Script – Calls the above functions and outputs the final cleaned datasets.
No intermediate outputs (e.g., consort, consort_midpoint6, output.rds) will be generated after the Quality Assurance step.
Final cleaned datasets will be produced for each cohort (prevax, vax, unvax).
The text was updated successfully, but these errors were encountered: