Adjusted Mean

Statistical averages that have been corrected to compensate for data imbalances. Outliers, present in data sets will often be removed as they have a large impact on the calculated means of small populations; an adjusted mean can be determined by removing these outlier figures. Adjusted means are also called "least squares means" and are calculated using a multiple regression equation.

For example, in studying both men and women who participate in a particular behavior or activity, it may be necessary to adjust the data to account for the impact of gender on the results. Without using adjusted means, results that might at first seem attributable to participating in a certain activity or behavior could be skewed by the impact of participants' gender. In this example, men and women would be considered covariates, a type of variable that the researcher cannot control but that affects an experiment's results. Using adjusted means compensates for the covariates to see what the affect of the activity or behavior would be if there were no differences between the genders.