What are the effects of missing data on research outcomes?
Missing data can lead to biased results, reduced statistical power, and can affect the validity of research conclusions.
Can you give examples of how missing data has impacted specific studies?
Sure! In clinical trials, missing patient data can skew the effectiveness of a treatment, leading to incorrect conclusions.
How can researchers handle missing data?
Researchers can use techniques like imputation, sensitivity analysis, or design studies to minimize the impact of missing data.
Are there any tools available to help with missing data analysis?
Yes, there are several tools like R packages and Python libraries that can assist in analyzing and handling missing data.
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