Collaborative Institutional Training Initiative (CITI) Social and Behavioral Research Practice Exam

Employing random sampling techniques is a fundamental way to mitigate bias in research studies. By randomly selecting participants from a larger population, researchers ensure that every individual has an equal chance of being included in the sample. This helps to eliminate selection bias, as it reduces the likelihood that certain types of people are overrepresented or underrepresented in the study. When the sample is representative of the broader population, the findings are more likely to be valid and generalizable. Random sampling contributes to the integrity of the research by maximizing diversity and minimizing potential confounding variables, which ultimately enhances the reliability of the conclusions drawn from the data.

In contrast, using subjective measures exclusively can introduce personal biases and limit the objectivity of the outcomes. Focusing solely on qualitative data may overlook the benefits of quantitative measures that can offer a more comprehensive understanding. Avoiding participant feedback disregards the value of obtaining perspectives from those directly involved, which can lead to a narrow understanding of the research question being studied. Hence, employing random sampling is a rigorous approach to fostering unbiased results in research.