Canadian Health Information Management Association Exam 2025 – 400 Free Practice Questions to Pass the Exam

In quantitative research, control measures are primarily used to avoid bias. Bias refers to systematic errors that can affect the validity of research findings. It can arise from various sources, including how data is collected, how subjects are selected, or even how results are analyzed. Control measures, such as random sampling, blinding, and using control groups, help ensure that the results are a true reflection of the phenomenon being studied instead of being skewed by extraneous factors.

By minimizing bias, researchers can enhance the reliability and generalizability of their findings, making their conclusions more robust and applicable to broader populations. This is crucial for maintaining the integrity of the research process and ensuring that any conclusions reached are based on accurate data rather than influenced by subjective or external elements.

The other options, while relating to research methodology, do not capture the primary focus of control measures in the context of avoiding systematic errors like bias. Duplication pertains to repetition in research efforts that are not necessary for a study, homogeneity refers to uniformity in a sample, and randomization is a technique used within control measures rather than an outcome to avoid.