What is Nonresponse Bias?
Nonresponse bias occurs when people who do not participate in a survey or study have different characteristics or opinions than those who do participate. In this situation, the sample data overrepresent the subpopulations who tend to respond instead of reflecting the whole population.
When respondents and non-respondents differ, the conclusions drawn from the survey might not accurately reflect the opinions or characteristics of the whole population. This condition can have serious consequences, such as making incorrect decisions based on the survey results.
Nonresponse bias is a form of sampling bias. Learn more about Sampling Bias: Definition & Examples.
Individuals with the following characteristics might be less likely to participate in a study:
- Less free time (e.g., having less flexible jobs or working multiple part-time jobs).
- Lower access to technology or transportation.
- Language barriers.
- Have health conditions.
- Low interest in the subject matter.
Nonresponse bias is a common problem in survey research because it is virtually impossible to get a 100% response rate. In fact, most response rates are less than 50%, and researchers typically consider 30% to be “good.” In other words, a survey with a reasonable response rate might still have 70% of the sample who don’t respond.
Read on to learn how to reduce nonresponse bias before and during a study and how to adjust for it afterward.
Related post: Selection Bias: Definition & Examples
Nonresponse Bias Example
Researchers conducted a survey to understand the opinions about recent changes to the public transportation system in the city. The survey used phone calls and online forms. Afterward, the researchers find that the response rate from people above 65 is much lower than other age groups. They might not have responded due to difficulties in using technology to access the online forms or reluctance to answer phone calls from unknown numbers.
As a result, the survey results might not accurately represent the attitudes of the entire population by underrepresenting the opinions of the elderly, who may have a different perspective on the changes.
Reducing Nonresponse Bias
Reducing nonresponse bias requires implementing proactive strategies that increase response rates and ensure that the sample is representative of the target population. Typically, the methods for minimizing nonresponse bias address the characteristics of non-responders I list above. You can implement the following types of things while designing and conducting the survey.
Good Survey Design
A short and easy-to-understand survey design is excellent for reducing nonresponse bias because it is less likely to overwhelm or frustrate participants, making them more willing to complete the survey. As the length and complexity increase, participation tends to decrease.
Target Relevant Group
When individuals are not interested in the subject matter, they are less likely to respond. Consequently, be sure you’re talking to the correct people!
Track and Send Reminders
Reduce nonresponse bias by tracking non-respondents and contacting them. Some will participate after the follow-up contacts, increasing the response rate.
Another way to minimize nonresponse bias is to use incentives to encourage participation. For example, surveys may offer participants a chance to win a prize or enter a drawing in exchange for completing the survey.
Use Multiple Contact Methods and Modes of Data Collection
One of the best ways to minimize nonresponse bias is to use multiple modes of data collection. For example, researchers can use both telephone and online forms to conduct the survey. This approach allows researchers to reach people who may not respond to one mode of data collection but may respond to another. You can also contact people using their native languages and employ translators.
Ensure Respondents Remain Anonymous
People value their privacy! Hence, reassuring potential participants that the study won’t link their data to their identities will help reduce nonresponse bias. This assurance is crucial when dealing with sensitive topics, such as health conditions and social taboos.
Assessing Nonresponse Bias After Data Analysis
So, you’ve completed your survey or other study and suspect that nonresponse bias might be a problem. What can you do? The priority is to understand the magnitude and scope of the problem. Then, you can interpret your sample results in that context.
Start by calculating the nonresponse rate to evaluate the size of the potential problem. If participants return 30% of your surveys, you know that the nonresponse rate is 100% – 30% = 70%. Unfortunately, there’s plenty of potential for bias!
Then assess late respondents because they can look like nonrespondents. Understand this group’s characteristics because it gives you an idea about those who didn’t respond at all. Are they systematically different from those who responded earlier? If they’re not different in relevant attributes, you might not have a problem!
Additionally, use some exceptional effort to follow up with some nonrespondents. Your goal is to gather at least some information from them. You just need enough data to understand how they differ from the respondents.
These steps will help you understand the direction and magnitude of the nonresponse bias in your study. If you obtain enough information, you might be able to statistically modify your findings to factor in non-respondents. For instance, you might use weighted averages to adjust the raw sample means. Learn more about Weighted Averages.