A study on alcohol consumption by Lahaut and colleagues illustrates the danger of non-response bias. After receiving responses from only about half of their mail survey sample, the researchers conducted unannounced home visits to the non-responders. They discovered that these original non-responders included a high proportion of abstainers. If the researchers had relied solely on the original responders, their estimates of alcohol consumption would have been artificially inflated.

Alcohol Consumption Survey Example

The most effective approach to minimizing non-response bias is to proactively reduce the number of non-responders by maximizing the survey's overall response rate. Although statistical techniques exist to correct for non-response bias after data collection, these corrections rely on assumptions about the non-participating individuals that might be entirely incorrect, making prevention the superior strategy.

Minimizing Non-response Bias

Researchers can attempt to statistically correct for non-response bias, but this method relies on making assumptions about the individuals who did not participate. For instance, a correction might assume that non-responders are demographically or behaviorally similar to late responders. Because these underlying assumptions may be incorrect, statistical correction is generally considered less reliable than proactively minimizing the number of non-responders.

Statistical Correction for Non-response Bias

Which of the following best defines non-response bias in a research survey?

Non-response bias is a specific form of sampling bias that occurs when individuals who choose not to participate in a survey differ systematically from those who do complete it. Even when a study employs careful random sampling, this bias can skew results and lead to inaccurate conclusions because the final respondents no longer accurately represent the original intended sample.

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Sampling bias is a systematic error that occurs when the method used to select participants results in a sample that fails to accurately represent the broader target population. Because the selected individuals differ in important ways from the overall group, any statistical findings derived from this unrepresentative sample will likely be inaccurate and cannot be safely generalized.

Sampling Bias

A survey non-responder is an individual selected for a survey sample who fails to complete the questionnaire. This lack of participation can occur for various reasons, including moving away, being too busy, lacking interest in the topic, or refusing to participate on principle.

Survey Non-responder

https://kpu.pressbooks.pub/psychmethods4e/

KPU Research Methods in Psychology - 4th American Edition


**Context**: Let's say we have a neurologist from Hospital X who wants to investigate the relationship between cancer and stroke risk in the general population with a case-control study. The cases are all the neurologist's patients with a history of strokes. The control group consists of all her patients without a stroke history. Both groups were assessed for cancer. 

**How it Relates to Selection Bias**: Patients in the hospital may be more predisposed to those conditions or may have been brought to the hospital for those conditions. Therefore, they may be overrepresented in the study compared to the general population.

Example: Selection Bias in Case-Control Studies

Take Tobacco case as an example, the number of cancer patients admitted to hospital is by no means representative of the entire population, or even of smokers.

Another example of selection bias in Case-control Studies


- The COVID-19 testings tend to focus on already hospitalized people, not accounting for the people with mild symptoms and the asymptomatics leading to selection bias.  
- The differences in death rates across countries may not be attributed to clinical, demographic, and environmental factors.  
- Together with random sampling/testing, the Bayesian Network model allows causal explanations from data for better predictions.  


Summary of "COVID-19 infection and death rates: the need to incorporate causal explanations for the data and avoid bias in testing"

Non-response Bias

The 1936 Literary Digest straw poll was a survey conducted to predict the outcome of the presidential election between Alf Landon and Franklin Roosevelt. The magazine attempted to forecast the results by sending ballots, which were also subscription requests, to millions of Americans. Based on this method, the editors incorrectly predicted that Landon would win in a landslide.

1936 Literary Digest Straw Poll

What type of systematic error occurs when the method used to select participants results in a sample that fails to accurately represent the broader target population?

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