When analyzing the dataset, researchers controlled for several covariables to isolate the treatment effect.

In the regression analysis, we treated age as a covariable to adjust for potential confounding.

Age was identified as a covariable predictor of recovery time, so we adjusted for it in the regression.

The researchers measured the covariation between temperature and crop yield to understand their relationship.

When analyzing ecological data, researchers must account for covariations between species abundance and climate variables to avoid misleading conclusions.

The regression model adjusted for several covariates to isolate the treatment effect.

Over the decade, the two indicators covaried, reflecting how closely their fluctuations were linked.

In the experiment, plant stress covaries with soil moisture as sunlight increases.

In the regression model, age was included as a covariate to control for its effect on blood pressure.

The researchers debated whether the term covariancy accurately reflected the relationship between the two variables.