What method can be used at the analysis stage to reduce confounding?

The appropriate method to reduce confounding at the analysis stage is through direct standardization. This technique involves adjusting the results of a study to account for differences in the distribution of confounding variables across groups. By applying direct standardization, researchers can create a fair comparison between groups by controlling for these confounding factors, which can often skew results and lead to inaccurate conclusions.

In practice, this method allows for clearer insights into the relationship between primary exposure and outcome by eliminating variation caused by these confounders. It is especially useful in epidemiological studies where the composition of populations might differ significantly.

The other options represent methods that are useful in various contexts but do not specifically apply at the analysis stage. For example, randomized assignment of exposures is a method typically employed during the design phase of a study to prevent confounding from occurring in the first place. Matching subjects based on outcomes also occurs at the design stage, where researchers aim to balance the groups in terms of key characteristics. Lastly, using qualitative assessments may provide valuable context and insights but is not a statistical method for controlling confounding specifically during the analysis stage.