How to use Data Cleaning & Validation

Audit, clean and validate your dataset before any model is fitted, with a documented trail of every decision made along the way.

Before you start

• • A signed-in SciExpert account

Steps

1. 1

   Open Data Cleaning & Validation

   From the workspace sidebar choose Data Cleaning & Validation. On a phone, open the All menu and tap Data Cleaning & Validation.

2. 2

   Set up your inputs

   Audit, clean and validate your dataset before any model is fitted, with a documented trail of every decision made along the way. Start with the smallest realistic input so you can check the output before scaling up.

3. 3

   Run it

   Run the tool and check the first output: raw data auditing: missingness patterns, duplicate detection, logic checks.

4. 4

   Review what came back

   Work through the results: missing data handling with multiple imputation (mice, amelia) and sensitivity analysis; outlier identification using statistical and visual diagnostics; standardisation, variable coding, transformation and full cleaning documentation.

5. 5

   Save or export

   Save the configuration as a preset if you will repeat it, and export the output when you need it outside SciExpert. Your inputs persist across refreshes and sign-ins.

Tips

• • Start with a small input, verify the output, then scale up.
• • Save a preset once the configuration works so you can reuse it across papers.

Troubleshooting