Clinical Research Data Cleaning & Structuring for Statistical Analysis (Biostatistician Required)
I am conducting a clinical research study for a Masters in Anaesthesiology and require an experienced biostatistician or statistical analyst to clean, code, and structure my dataset in Microsoft Excel for formal statistical analysis.
The dataset is already collected but requires professional preparation to ensure it is analysis-ready and compatible with statistical software such as R, SPSS, or Stata.
Scope of Work:
ā¢ Clean raw dataset (resolve inconsistencies, duplicates, formatting errors)
ā¢ Standardise variable naming and formats
ā¢ Convert categorical variables into appropriate coded formats
ā¢ Handle missing data appropriately (define and apply consistent rules)
ā¢ Structure dataset according to best practices (one row per observation, one column per variable)
ā¢ Advise on long vs wide format (if repeated measures present)
ā¢ Create a clear, professional data dictionary/codebook
ā¢ Ensure dataset is ready for regression and/or comparative statistical analysis
Deliverables:
1. Cleaned dataset (.xlsx and .csv)
2. Data dictionary (codebook with variable definitions and coding schema)
3. Brief summary of changes made and any data limitations identified
Requirements:
ā¢ Proven experience in biostatistics, epidemiology, or clinical data analysis
ā¢ Strong working knowledge of R, SPSS, or Stata
ā¢ Experience with medical or clinical research datasets (essential)
ā¢ Ability to prepare datasets for publication-quality statistical analysis
Important (Location Requirement):
The raw data is currently paper-based and cannot be digitised or shared remotely. Therefore, applicants must be based in Cape Town and able to access the data in person.
To Apply, Please Include:
ā¢ A brief description of similar clinical datasets you have worked on
ā¢ An example of a dataset/codebook you have created (anonymised)
Timeline:
Flexible but ideally within 1ā2 weeks
Note:
This is not basic Excel work. Only applicants with relevant statistical/clinical data experience will be considered.
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The dataset is already collected but requires professional preparation to ensure it is analysis-ready and compatible with statistical software such as R, SPSS, or Stata.
Scope of Work:
ā¢ Clean raw dataset (resolve inconsistencies, duplicates, formatting errors)
ā¢ Standardise variable naming and formats
ā¢ Convert categorical variables into appropriate coded formats
ā¢ Handle missing data appropriately (define and apply consistent rules)
ā¢ Structure dataset according to best practices (one row per observation, one column per variable)
ā¢ Advise on long vs wide format (if repeated measures present)
ā¢ Create a clear, professional data dictionary/codebook
ā¢ Ensure dataset is ready for regression and/or comparative statistical analysis
Deliverables:
1. Cleaned dataset (.xlsx and .csv)
2. Data dictionary (codebook with variable definitions and coding schema)
3. Brief summary of changes made and any data limitations identified
Requirements:
ā¢ Proven experience in biostatistics, epidemiology, or clinical data analysis
ā¢ Strong working knowledge of R, SPSS, or Stata
ā¢ Experience with medical or clinical research datasets (essential)
ā¢ Ability to prepare datasets for publication-quality statistical analysis
Important (Location Requirement):
The raw data is currently paper-based and cannot be digitised or shared remotely. Therefore, applicants must be based in Cape Town and able to access the data in person.
To Apply, Please Include:
ā¢ A brief description of similar clinical datasets you have worked on
ā¢ An example of a dataset/codebook you have created (anonymised)
Timeline:
Flexible but ideally within 1ā2 weeks
Note:
This is not basic Excel work. Only applicants with relevant statistical/clinical data experience will be considered.
Apply tot his job
Apply To this Job