In which scenario would a researcher expect to encounter non-response bias?

Non-response bias occurs when certain groups of individuals do not respond to a survey, leading to results that may not accurately represent the overall population. In the context of survey research, if specific demographic groups (such as minorities, elderly individuals, or lower-income respondents) are less likely to participate, the perspectives and values of those groups are underrepresented. This can skew the findings and limit the generalizability of the results, ultimately affecting the study’s conclusions.

In this scenario, the situation described directly points to the possibility of non-response bias, as the absence of responses from particular groups can lead to a significant gap in understanding the complete picture that the survey is trying to capture. Other options would not lead to such biases: if all subjects respond, then the data is complete; if subjects are randomly selected, there’s no bias introduced through selection; and if subjects are forced to answer, everyone is included in the dataset, reducing the risk of non-response bias. Thus, failure to obtain responses from specific groups clearly illustrates the essence of non-response bias.