D.designdata: Construct Density Design Data
Usage
D.designdata (mask, Dmodel, grouplevels, sessionlevels, sessioncov =
NULL, meanSD = NULL)
Arguments
Dmodel
formula for density model
grouplevels
vector of group names
sessionlevels
vector of character values for session names
sessioncov
optional dataframe of values of session-specific
covariate(s).
meanSD
optional external values for scaling x- and
y- coordinates
Value
- Dataframe with one row for each combination of mask point, group and
session. Conceptually, we use a 3-D rectangular array with enough rows
to accommodate the largest mask, so some rows in the output may merely
hold space to enable easy indexing. The dataframe has an attribute
`dimD' that gives the relevant dimensions:
attr(dframe, "dimD") =
c(nmask, ngrp, R), where nmask is the number of mask points,
ngrp is the number of groups, and R is the number of
sessions. Columns correspond to predictor variables in Dmodel.
The number of valid rows (points in each session-specific mask) is
stored in the attribute `validMaskRows'.
For a single-session mask, meanSD is a 2 x 2 matrix of mean and
SD (rows) for x- and y-coordinates. For a multi-session mask, a list of
such objects. Ordinarily these values are from the meanSD attribute of
the mask, but they must be specified when applying a new mask to an
existing model.
Details
This is an internal secr function that you are unlikely ever to
use. Unlike secr.design.MS, this function does not
call model.matrix.