Factor information table for Fit Mixed Effects Model

Find definitions and interpretation guidance for every statistic in the factor information table.

The factor information table displays the factors in the design, the type of factors, the number of levels, and the values of the levels.

Factors are the variables that you control in the experiment. Factors are also known as independent variables, explanatory variables, and predictor variables. Factors can assume only a limited number of possible values, known as factor levels. Factors can take text or numeric values. Numeric factors use a few controlled values in the experiment, even though many values are possible.


Use the factor information table to verify that you performed the analysis as you intended.

In a mixed effects model, factors can be either fixed or random. In general, if the investigator controls the levels of a factor, the factor is fixed. On the other hand, if the investigator randomly sampled the levels of a factor from a population, the factor is random.

For example, a quality analyst plans to study factors that could affect plastic strength during the manufacturing process. The analyst includes Additive, Temperature, and Operator in the experiment. The additive is a categorical variable which can be type A or type B. Temperature is a continuous variable but the analyst plans to include only three temperatures settings in the experiment: 100 °C, 150 °C, and 200 °C. Because the analyst controls the levels of these two factors in the experiment, these factors are both fixed. On the other hand, the analyst decides to randomly select operators from the plant population. Therefore, Operator is a random factor.

Factor Additive Temperature Operator
Type Fixed Fixed Random
Level A Low (100 °C) A
Level B Medium (150 °C) B
Level   High (200 °C) C

Factors can be crossed or nested. Factor A is crossed with factor B, denoted by A*B, when at each level of factor A, the levels of factor B are identical. Factor B is nested under factor A, denoted by B(A), when the levels of factor B are similar but not identical for different levels of factor A.

For example, if a design contains machine and operator, these factors are crossed if all operators use all machines. However, operator is nested in machine if each machine has a different set of operators.

In the factor information table, parenthesis indicates nested factors. For example, Operator (Machine) indicates that operator is nested within machine.

For more information on factors, go to Factors and factor levels, What are factors, crossed factors, and nested factors?, and What is the difference between fixed and random factors?.

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