Coverage Error

Definition

Coverage error refers to the discrepancy between the target population and the sample population in a survey. It occurs when the survey fails to include certain segments of the target population, leading to biased results that do not accurately represent the entire population.

5 Must Know Facts For Your Next Test

1. Coverage error can arise when the sampling frame does not include all members of the target population, leading to certain groups being underrepresented or excluded.
2. Factors such as geographic location, socioeconomic status, and access to technology can contribute to coverage error if they are not adequately accounted for in the sampling process.
3. Coverage error can be particularly problematic in online surveys, where individuals without internet access or digital literacy may be excluded from the sample.
4. Strategies to mitigate coverage error include using multiple sampling frames, employing mixed-mode data collection methods, and conducting thorough population research to identify potential coverage issues.
5. Assessing and addressing coverage error is crucial for ensuring the validity and generalizability of survey findings, as it helps to ensure that the sample accurately represents the target population.

Review Questions

• Explain how coverage error can arise in the context of measuring public opinion.
  • Coverage error can occur in public opinion surveys when the sampling frame does not adequately represent the target population. For example, if a survey only includes individuals with landline telephones, it may exclude certain demographic groups, such as younger people or those from lower socioeconomic backgrounds, who are more likely to rely on mobile phones. This can lead to biased results that do not accurately reflect the opinions of the entire population.
• Describe strategies that researchers can use to minimize coverage error in public opinion surveys.
  • To minimize coverage error in public opinion surveys, researchers can employ several strategies, such as using multiple sampling frames (e.g., landline and mobile phone numbers), incorporating mixed-mode data collection methods (e.g., online, telephone, and in-person), and conducting thorough population research to identify potential coverage issues. Additionally, researchers can use weighting techniques to adjust the sample to better reflect the target population's demographics and characteristics.
• Analyze the potential implications of coverage error on the validity and generalizability of public opinion survey findings.
  • Coverage error can have significant implications for the validity and generalizability of public opinion survey findings. If certain segments of the population are systematically excluded from the sample, the survey results may not accurately represent the views and opinions of the entire target population. This can lead to biased conclusions and limit the ability to make reliable inferences about the broader population. Addressing coverage error is crucial for ensuring that survey findings are valid, representative, and can be generalized to the target population, which is essential for informing policymakers, political decision-making, and our understanding of public opinion.

Related terms

Target Population: The entire group of individuals or units that the researcher wants to study and make inferences about.

Sample Population: The subset of the target population that is actually included in the survey or study.

Sampling Frame: The list or source from which the sample is drawn, which should ideally cover the entire target population.