Adjusted mean is a mean adjusted for certain data that could lead to misinterpretation. If in the data, far from center there are some values, the mean won't work properly.
For example, try to calculate mean from values: 2, 3, 3, 4, 3, 4, 5, 2, 130. The last value will move average significantly. Mathematically it is correct, but in real life it is probable that 130 is an error or one-time value. Adjusted mean, known also as least-squares mean lets remove such outliers and present.
Mean is a measure that can be easily manipulated and thus misinterpreted. It should always be used together with standard deviation and other statistical measures.
- Kramer, C. Y. (1957). Extension of multiple range tests to group correlated adjusted means. Biometrics, 13(1), 13-18.