This function provides a reasonable default formula for linear model analyses of class design objects with response(s). Per default, the resulting formula refers to the first response in the design and is of design-type specific nature.
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an object of class
further arguments to function
character string giving the name of the response variable
(must be among the numeric columns from
degree of the model (1=main effects only, 2=with 2-factor interactions and quadratic effects, 3=with 3-factor interactions and up to cubic effects, ...
function for the
logical indicating whether the error dummies of a Plackett Burman design are to be used in the formula (ignored for all other types of designs).
formula creates an appropriate formula for many kinds of
objects, e.g. for data frames (try e.g.
as.formula uses function formula, but cannot take any additional
The method for class
design objects modifies the way a data frame
would normally be treated by the
formula function. This also carries through
to default linear models.
Without the additional arguments, the function creates the formula with the first
response from the
response.names element of the
The default degree depends on the type of design: it is
2 for all other design types
degree does not have an effect for response surface designs
ccd) and latin hypercube designs (type
where the function always creates the formula for a full second order model including quadratic
degree does have an effect, it is the exponent of the sum of all experimental factors,
i.e. it refers to the degree of interactions, not to powers of the variables themselves
(A+B+C)^2 for degree 2).
For designs with a block variable (types
the block variable enters the formula as a main effect factor without any interactions.
For 2-level designs with center points (types
the formula contains an indicator variable
center for the center points
that can is used for checking whether quadratic effects are needed.
For designs with repeated measurements (
repeat.only and parameter designs,
the default is to analyse aggregated responses. For more detail,
see the documentation of
For optimal designs, the formula is the model formula used in optimizing the design.
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