1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
|
# Design FEH 1Aug90, re-written 21Oct91
#
# Augments S formula language to include:
#
# name - name[i] = name of ith original variable in x
# label - label[i] = label of ith original variable (=name if none)
# assume - assume(original x)
# assume.code - coded version of assume (1-9, 9=added interaction)
# parms - parms(original x)
# for interaction effects parms[[i]] is a matrix with dim
# 3 x (1+# interaction terms). First element in pair
# is 1 if first factor is represented as an expanded
# non-linear term, 0 otherwise (this applies to polynomial,
# lspline, rcspline, scored). Second element applies to
# second factor in interaction effect. Third element
# applies to third factor (0 if second order interaction)
# First column contains factor numbers involved in interaction.
# limits - limits(original x)
# values - For continuous variables with <=10 unique values, is
# vector of values. NULL otherwise.
# interactions - 3 x k matrix of factor numbers
#
# Cannot have interactions between two stratification factors.
#
#
Design <- function(mf, allow.offset=TRUE, intercept=1)
{
Terms <- attr(mf, "terms")
Term.labels <- attr(Terms,'term.labels')
iscluster <- if(length(Term.labels))
substring(Term.labels,1,8)=='cluster(' else FALSE
## Handle cluster() for cph
if(any(iscluster))
{
clustername <- Term.labels[iscluster]
cluster <- mf[[clustername]]
mf[[clustername]] <- NULL
Terms <- Terms[!iscluster]
Term.labels <- Term.labels[!iscluster]
}
else cluster <- NULL
## Problem: offsets not included in term.labels in R
##For some reason, model frame sometimes has a blank name if using %ia%
namx <- names(mf)
if(any(namx==""))
{
namx <- names(mf) <- c(namx[1],Term.labels)
dimnames(mf)[[2]] <- namx
dimnames(attr(Terms,"factors"))[[1]] <- namx
}
wts <- if(any(namx=='(weights)'))(1:length(namx))[namx=='(weights)']
else 0
if(length(Terms)==0) inner.name <- NULL
else
{
##Handle case where a function has two arguments that are names,
##e.g. rcs(x,knots) -> want x only
inner.name <- unique(var.inner(Terms))
## var.inner is stripped down version of terms.inner (see Design.trans)
##Note: these exclude interaction terms and %ia% terms
}
response.pres <- attr(Terms, 'response') > 0
offs <- attr(Terms, "offset")
if(!length(offs)) offs <- 0
if(offs>0 & !allow.offset)
stop("offset variable not allowed in formula")
factors <- attr(Terms, "factors")
if(length(factors) && response.pres) factors <- factors[-1,,drop=FALSE]
attr(Terms, "intercept") <- intercept
fname <- flabel <- name <- strt <- asm <- len <-
fname.incl.dup <- ia <- funits <- NULL
parm <- nonlinear <- limits <- values <- list()
scol<-1
colnam <- list()
XDATADIST <- .Options$datadist
if(length(XDATADIST))
{
if(!exists(XDATADIST)) stop(paste("dataset",XDATADIST,
"not found for options(datadist=)"))
datadist <- if(.R.) eval(as.name(XDATADIST)) else
eval(as.name(XDATADIST), local=FALSE)
Limits <- datadist$limits
Limnames <- dimnames(Limits)[[2]]
}
nc <- 0
options(Design.attr=NULL, TEMPORARY=FALSE)
##Used internally by asis, rcs, ...
anyfactors <- ncol(mf) > 1*response.pres
i1.noia <- 0
if(anyfactors)for(i in (response.pres+1):ncol(mf))
{
if(i != offs && i !=wts)
{
i1 <- i - response.pres
xi <- mf[[i]]
z <- attributes(xi)
assu <- z$assume.code
if(!length(assu) || assu!=9) i1.noia <- i1.noia+1
if(!length(assu))
{
## Not processed w/asis,et
nam <- inner.name[i1.noia]
lab <- attr(xi, "label")
ord <- is.ordered(xi) && all.is.numeric(levels(xi))
if(!length(lab) || lab=="") lab <- nam
if(ord)
{
xi <- scored(xi, name=nam, label=lab)
attr(mf[,i],"contrasts") <- attr(xi,"contrasts")
}
else if(is.character(xi) | is.category(xi))
{
if(is.ordered(xi) &&
.Options$contrasts[2]!='contr.treatment')
warning(paste('Variable',nam,'is an ordered factor.\n',
'You should set options(contrasts=c("contr.treatment","contr.treatment"))\nor Design will not work properly.'))
xi <- catg(xi, name=nam, label=lab)
}
else if(is.matrix(xi)) xi <- matrx(xi, name=nam, label=lab)
else xi <- asis(xi, name=nam, label=lab)
z <- c(z,attributes(xi))
}
za <- z$assume.code
zname <- z$name
fname.incl.dup <- c(fname.incl.dup, zname)
if(!length(fname) || !any(fname==zname))
{ # unique factor
nc <- nc+1
fname <- c(fname,zname)
flabel <- c(flabel,z$label)
asm <- c(asm,za)
colnam[[i1]] <- z$colnames
if(za!=8) name <- c(name, colnam[[i1]])
if(za!=9)
{
funits <- c(funits, if(length(z$units))z$units else '')
if(length(z$parms)) parm[[zname]] <- z$parms
if(length(XDATADIST))
{
limits[[zname]] <- if(any(Limnames==zname))
{
j <- match(zname, Limnames, 0) #require EXACT match
Limits[,j[j>0]]
}
else rep(NA,7)
j <- match(zname, names(datadist$values), 0)
if(j>0)
{
values[[zname]] <- datadist$values[[j]]
l1 <- levels(xi); l2 <- datadist$values[[j]]
if(length(l1) && ((length(l1) != length(l2)) ||
any(sort(l1) != sort(l2))))
warning(paste('Variable',zname,'has levels',paste(l1,collapse=' '),
'which do not match levels given to datadist (',
paste(l2,collapse=' '),'). datadist values ignored.'))
values[[zname]] <- l1
}
}
}
if(length(nonl <- z$nonlinear)) nonlinear[[zname]] <- nonl
if(za==9)
{
iia <- match(z$ia, fname)
if(any(is.na(iia)))stop(paste(paste(z$ia,collapse=" "),
"cannot be used in %ia% since not listed as main effect"))
ia <- cbind(ia, c(iia,0))
parms <- rbind(z$parms,0)
parms[,1] <- c(iia,0)
if(length(parms)) parm[[zname]] <- parms
}
}
nrows <- if(is.matrix(xi))nrow(xi) else length(xi)
}
}
##Save list of which factors where %ia% interactions
## (before adding automatic ias)
which.ia <- (1:length(asm))[asm==9]
##Add automatically created interaction terms
if(anyfactors)
{
nrf <- if(!length(factors)) 0 else if(.R.) nrow(factors) else
nrow(factors) * (ncol(factors) > 0)
## S-Plus, if only offset in model, has factors as 2 rows 0 cols
if(nrf || length(fname.incl.dup))
if((nrf-(offs > 0)) != length(fname.incl.dup))
stop("program logic error 1")
if(length(factors)) for(i in 1:ncol(factors))
{
f <- factors[,i]
j <- (1:length(f))[f>0]
nia <- length(j)
if(nia>1)
{
fn <- fname.incl.dup[j]
jf <- match(fn,fname.incl.dup)
if(any(is.na(jf))) stop("program logic error 2")
nc <- nc + 1
asm <- c(asm,9)
if(nia==2)ialab <- paste(fn[1],"*",fn[2])
else if(nia==3)ialab <- paste(fn[1],"*",fn[2],"*",fn[3])
else stop("interaction term not second or third order")
fname <- c(fname, ialab)
flabel <- c(flabel, ialab)
if(sum(asm[jf]==8)>1)
stop("cannot have interaction between two strata factors")
nn <- list()
for(k in 1:nia)
{
if(asm[jf[k]]==5 | asm[jf[k]]==8)
nn[[k]] <- paste(fn[k],"=",parm[[fname[jf[k]]]][-1],sep="")
else if(asm[jf[k]]==7)
{
nn[[k]] <- c(fn[k],
paste(fn[k],"=",
parm[[fname[jf[k]]]][c(-1,-2)],sep=""))
}
else nn[[k]] <- colnam[[jf[k]]]
}
if(nia==2) nn[[3]] <- ""
parms <- jf
if(length(jf)==2) parms <- c(parms, 0)
nonlin <- NULL
nl1 <- nonlinear[[fname[jf[1]]]]
nl2 <- nonlinear[[fname[jf[2]]]]
##Strata factors don't have nonlinear duplicated for # levels - 1
if(asm[jf[1]]==8)
nl1 <- rep(FALSE, length(parm[[fname[jf[1]]]])-1)
if(asm[jf[2]]==8)
nl2 <- rep(FALSE, length(parm[[fname[jf[2]]]])-1)
if(nia==2) nl3 <- FALSE
else if(asm[jf[3]]==8)
nl3 <- rep(FALSE, length(parm[[fname[jf[3]]]])-1)
else nl3 <- nonlinear[[fname[jf[3]]]]
n1 <- nn[[1]]
n2 <- nn[[2]]
n3 <- nn[[3]]
##model.matrix makes auto-products move first variable fastest, etc.
for(j3 in 1:length(n3))
{
for(j2 in 1:length(n2))
{
for(j1 in 1:length(n1))
{
parms <- cbind(parms,c(nl1[j1],nl2[j2],nl3[j3]))
nonlin <- c(nonlin, nl1[j1] | nl2[j2] | nl3[j3])
if(nia==2)name <- c(name, paste(n1[j1],"*",n2[j2]))
else name <- c(name, paste(n1[j1],"*",n2[j2],"*",n3[j3]))
}
}
}
##If was 2-way interaction and one of the factors was restricted %ia%,
##adjust indicators
k <- match(jf, which.ia, 0)
if(any(k>0))
{
if(nia==3)
stop("cannot have 2-way interaction with an %ia% interaction")
k <- jf[k>0]
wparm <- parms[,1]==k; wparm[3] <- TRUE
parms[wparm,] <- parm[[fname[k]]][1:2,,drop=FALSE]
jf <- parms[,1]
nonlin <- apply(parms, 2, any)[-1]
}
if(length(jf)==2) {jf <- c(jf, 0); parms[3,] <- 0}
ia <- cbind(ia, jf)
if(length(parms)) parm[[ialab]] <- parms
if(length(nonlin)) nonlinear[[ialab]] <- nonlin
}
}
}
if(anyfactors)
{
if(length(XDATADIST))
limits <- structure(limits,
row.names=c("Low:effect","Adjust to",
"High:effect",
"Low:prediction","High:prediction",
"Low","High"),
class="data.frame")
##data.frame converts variables always NA to factor!
if(length(funits) != sum(asm!=9)) warning('program logic warning 1')
else names(funits) <- fname[asm!=9]
atr <- list(name=fname, label=flabel, units=funits, colnames=name,
assume=c("asis","polynomial","lspline","rcspline","category",
"","scored","strata","interaction","matrix")[asm],
assume.code=as.integer(asm), parms=parm, limits=limits,
values=values,nonlinear=nonlinear,
interactions=structure(ia,dimnames=NULL))
nact <- attr(mf, 'na.action')
if(length(nact) && length(nmiss <- nact$nmiss))
{
jia <- grep('%ia%',names(nmiss), fixed=TRUE)
if(length(jia)) nmiss <- nmiss[-jia]
jz <- which(names(nmiss) != '(weights)')
if(response.pres) jz <- jz[jz > 1]
names(nmiss)[jz] <- fname[asm != 9]
attr(mf, 'na.action')$nmiss <- nmiss
}
}
else atr <- list(name=NULL, assume=NULL, assume.code=NULL, parms=NULL)
attr(mf, 'Design') <- atr
attr(mf, 'terms') <- Terms
if(length(cluster)) attr(mf, 'cluster') <- cluster
mf
}
|
