In epidemiology, collecting accurate and relevant data is crucial for understanding the distribution and determinants of health and diseases in populations. Skip logic helps in:
Reducing respondent burden: By directing respondents only to relevant questions, it minimizes fatigue and dropout rates. Improving data quality: It ensures that respondents do not answer questions that are not applicable to them, thereby reducing noise in the data. Streamlining data analysis: With fewer irrelevant responses, the data analysis process becomes more straightforward and meaningful.
