Publication date: 08/13/2020

Experiments with Covariates

Sometimes measurements on the experimental units that are intended for an experiment are available. These measurements might affect the experimental response. It is useful to include these variables, called covariates, as design factors. Although you cannot directly control these values, you can ensure that the levels of the other design factors are chosen to yield the most precise estimates of all the effects.

The Custom Design platform constructs a design that selects covariate values in an optimal fashion. Covariate values are selected from an existing data table that provides covariate information about the potential experimental units. You can specify a number of runs that is smaller than the number of experimental units listed in your data table. You can also specify covariates that are hard-to-change. When you make your design and the design has fewer runs than the number of rows in the covariate table, the design table includes a Covariate Row Index column.This column indicates the row from the covariate table that corresponds to each experimental run.

Note: The number of rows in the covariate data table where covariate factors have nonmissing values must be greater than or equal to the specified Number of Runs.

Design with Fixed Covariates

Design with Hard-to-Change Covariates

Design with a Linear Time Trend

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