In nonrandomized evaluations, what is a key method to reduce confounding when comparing groups?

• A. Matching treatment and comparison groups on observed characteristics.
• B. Increasing sample size.
• C. Blind assessment.
• D. Using only qualitative data.

Answer: (A)

When a study isn’t randomized, groups can differ in factors that influence the outcome. Matching treatment and comparison groups on observed characteristics is a key way to reduce that confounding bias because it makes the groups more comparable on those factors. By pairing or aligning units with similar covariates across treated and untreated groups, the analysis compares like with like, so differences in the outcome are more likely attributable to the treatment rather than preexisting differences. Of course, matching only accounts for observed characteristics; unobserved confounders may still bias results, so researchers may combine matching with other methods like regression adjustment or propensity scores. Increasing sample size helps precision but doesn’t address systematic differences between groups. Blind assessment helps limit measurement bias, not confounding. Using only qualitative data doesn’t address confounding either.