Choosing the right tool often depends on the specific requirements of the epidemiological study, such as the complexity of the data, the size of the dataset, and the level of expertise of the researcher. Here are a few considerations:
Complexity of Data: For complex datasets, tools like R or Python are more suitable due to their advanced functionalities. Size of Dataset: For very large datasets, SQL and Python's libraries like Dask can handle large volumes of data efficiently. User Expertise: For users with limited programming knowledge, Excel or OpenRefine may be more accessible.
