IAPlot: Main Effects and Interaction Plots

Description Usage Arguments Details Value Author(s) References See Also

View source: R/IAPlot.R

Description

Main effects plots and interaction plots are produced. The other documented functions are not intended for users.

Usage

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MEPlot(obj, ...)
## S3 method for class 'design'
MEPlot(obj, ..., response = NULL)
## Default S3 method:
MEPlot(obj, main = paste("Main effects plot for", respnam), 
    pch = 15, cex.xax = par("cex.axis"), cex.yax = cex.xax, mgp.ylab = 4, 
    cex.title = 1.5, cex.main = par("cex.main"), 
    lwd = par("lwd"), abbrev = 3, select = NULL, ...)

IAPlot(obj, ...)
## S3 method for class 'design'
IAPlot(obj, ..., response = NULL)
## Default S3 method:
IAPlot(obj, main = paste("Interaction plot matrix for", respnam), 
    pch = c(15, 17), cex.lab = par("cex.lab"), cex = par("cex"), 
    cex.xax = par("cex.axis"), cex.yax = cex.xax, cex.title = 1.5, 
    lwd = par("lwd"), abbrev = 4, select = NULL, show.alias = FALSE, ...)
         
intfind(i, j, mat)

check(obj)

remodel(obj)

Arguments

obj

an experimental design of class design with the type element of the design.info attribute containing “FrF2” or “pb”
OR
a linear model object with 2-level factors or numerical 2-level variables;
the structure must be such that effects are either fully aliased or orthogonal, like in a regular fractional factorial 2-level design;
note that IAPlot currently requires the response in obj to be a pre-defined variable and not a calculated quantity

...

further arguments to be passed to the default function;
... in the default method are not used, they have been added because of formal requirements only

response

character string that specifies response variable to be used, must be an element of response.names(obj); if NULL, the first response from response.names(obj) is used

main

overall title for the plot assembly

pch

Plot symbol number MEPlot, or vector of two plot symbol numbers for the lower and higher level of the trace factor iap

cex.xax

size of x-axis annotation, defaults to cex.axis-parameter

cex.yax

size of y-axis annotation, defaults to cex.xax

mgp.ylab

horizontal placement of label of vertical axis in MEPlot

cex.title

multiplier for size of overall title (cex.main is multiplied with this factor)

cex.main

size of individual plot titles in MEPlot

cex.lab

Size of variable names in diagonal panels of interaction plots produced by IAPlot.

cex

size of plot symbols in interaction plots

lwd

line width for plot lines and axes

abbrev

number of characters shown for factor levels

select

vector with position numbers of the main effects to be displayed;
default: all main effects; the default implies the full interaction plot matrix for IAPlot.
For IAPlot, the full interaction plot matrix for the selected factors is displayed. Of course, at least two factors must be selected. Furthermore, the linear model obj must at least contain one interaction term among the selected variables. For interactions that do not occur in the linear model, not plot is shown. An interaction plot matrix of data means can be obtained by specifying the model with all possible 2-factor interactions (e.g. formula y~(.)^2 for a regular 2-level fractional factorial, for which y is the only response and all other variables are 2-level factors).

show.alias

if TRUE, the interaction plot shows the number of the list entry from aliases(obj)\$aliases (cf. aliases) in order to support immediate diagnosis of which depicted interaction may be due to other than the shown effect because of aliasing;
CAUTION: if the select option is used, the model is reduced to the selected factors, i.e. aliases with unselected factors are not shown!

i

integer, for internal use only

j

integer, for internal use only

mat

matrix, for internal use only

Details

For functions MEPlot or IAPlot, if obj is a design with at least one response variable rather than a linear model fit, the lm-method for class design is applied to it with the required degree (1 or 2), and the default method for the respective function is afterwards applied to the resulting linear model.

MEPlot

produces plots of all main effects in the model, or selected ones if select is specified

IAPlot

produces plots of all interaction effects in the model, or selected ones if select is specified

intfind

is an internal function not directly useful for users

check

is an internal function for checking whether the model complies with assumptions (fractional factorial of 2-level factors with full or no aliasing, not partial aliasing; this implies that Plackett-Burman designs with partial aliasing of 2-factor interactions give an OK (=TRUE) in check for pure main effects models only.)

remodel

is an internal function that redoes factor values into -1 and 1 coding, regardless of the contrasts that have been used for the original factors; numerical data are transformed by subtracting the mean and dividing by half the range (max-min), which also transforms them to -1 and 1 coding in the 2-level case (and leads to an error otherwise)

Value

MEPlot and IAPlot invisibly return the plotted effects (two-row matrix or four-row matrix, respectively). If show.alias=TRUE, the matrix returned by IAPlot has as the attribute aliasgroups, which contains all alias groups (list element number corresponds to number in the graphics tableau).

The internal function check is used within other functions for checking whether the model is a fractional factorial with 2-level factors and no partial aliasing, as requested for the package to work. It is applied to remodeled objects only and returns a logical. If the returned value is FALSE, the calling function fails.

The internal function intfind returns an integer (length 1 or 0). It is not useful for users.

The internal function remodel is applied to a linear model object and returns a list of two components:

model

is the redone model with x-variables recoded to numeric -1 and 1 notation and aov objects made into “pure” lm objects

labs

is a list preserving the level information from original factors (levels are minus and plus for numerical variables)

Author(s)

Ulrike Groemping

References

Box G. E. P, Hunter, W. C. and Hunter, J. S. (2005) Statistics for Experimenters, 2nd edition. New York: Wiley.

See Also

FrF2-package for examples


FrF2 documentation built on July 2, 2020, 2:24 a.m.