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Mortality Definition

Loss of test units or subjects during the course of a study. The problem is that those lost may be systematically different from those who stay. Often called attrition.

In market research, mortality refers to participant dropout or attrition from a study before its completion. This loss of participants can affect the validity and reliability of the results, as the final sample may not fully represent the original group or intended audience.

Who relies on mortality in market research?                

Market researchers, project managers, data analysts and statisticians rely on tracking mortality rates to assess the quality and integrity of the study. Understanding mortality is essential for researchers conducting longitudinal studies or multi-session surveys where participant retention is crucial.

What are the key aspects of mortality in market research? 

Key aspects include:

• Participant attrition: The rate and reasons for dropout during a study.
• Impact on sample size: Reduces the number of participants, potentially impacting statistical power.
• Bias potential: Can lead to non-representative results if certain types of participants are more likely to drop out.
• Data quality: Affects the reliability and validity of the findings.
• Retention strategies: Methods to minimize dropout and improve study completion rates.

Why is mortality important in market research?        

Mortality is important because participant dropout can lead to biased results and reduce the generalizability of the findings. By understanding and managing mortality, researchers can ensure more accurate, reliable and representative data, which is critical for making sound decisions based on the study results.

How do market researchers use mortality?  

Market researchers monitor mortality rates to identify patterns in participant dropout, implement retention strategies and adjust study designs if necessary. They may use incentives, reminders or follow-up communication to reduce mortality. In analysis, researchers may also use statistical techniques to account for attrition and mitigate its impact on the study results.