revise Define what constitutes exposure and outcomes in precise, scientific terms. This helps in maintaining consistency and reducing ambiguity. Balancing Sensitivity and Specificity: Sensitivity: Ensure that the criteria are sensitive enough to identify all relevant cases. Specificity: Ensure that the criteria are specific enough to exclude non-relevant cases. Random Sample Representation: Random Sampling: Use random sampling techniques to ensure that the sample is representative of the population. This helps in minimizing selection bias. Standardized Procedures: Interviewing and Questioning: Develop and adhere to standardized protocols for interviewing and questioning participants. This ensures consistency across the study. Testing: Use agreed-upon definitions and procedures for testing both study groups to maintain uniformity. By following these steps, you can significantly reduce the risk of bias in your data collection and study design