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
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/multinomial.R
\name{multinomial}
\alias{multinomial}
\alias{kappa.multinomial}
\alias{kappa.table}
\alias{gkgamma}
\title{Estimate probabilities in contingency table}
\usage{
multinomial(
x,
data = parent.frame(),
marginal = FALSE,
transform,
vcov = TRUE,
IC = TRUE,
...
)
}
\arguments{
\item{x}{Formula (or matrix or data.frame with observations, 1 or 2 columns)}
\item{data}{Optional data.frame}
\item{marginal}{If TRUE the marginals are estimated}
\item{transform}{Optional transformation of parameters (e.g., logit)}
\item{vcov}{Calculate asymptotic variance (default TRUE)}
\item{IC}{Return ic decomposition (default TRUE)}
\item{...}{Additional arguments to lower-level functions}
}
\description{
Estimate probabilities in contingency table
}
\examples{
set.seed(1)
breaks <- c(-Inf,-1,0,Inf)
m <- lvm(); covariance(m,pairwise=TRUE) <- ~y1+y2+y3+y4
d <- transform(sim(m,5e2),
z1=cut(y1,breaks=breaks),
z2=cut(y2,breaks=breaks),
z3=cut(y3,breaks=breaks),
z4=cut(y4,breaks=breaks))
multinomial(d[,5])
(a1 <- multinomial(d[,5:6]))
(K1 <- kappa(a1)) ## Cohen's kappa
K2 <- kappa(d[,7:8])
## Testing difference K1-K2:
estimate(merge(K1,K2,id=TRUE),diff)
estimate(merge(K1,K2,id=FALSE),diff) ## Wrong std.err ignoring dependence
sqrt(vcov(K1)+vcov(K2))
## Average of the two kappas:
estimate(merge(K1,K2,id=TRUE),function(x) mean(x))
estimate(merge(K1,K2,id=FALSE),function(x) mean(x)) ## Independence
##'
## Goodman-Kruskal's gamma
m2 <- lvm(); covariance(m2) <- y1~y2
breaks1 <- c(-Inf,-1,0,Inf)
breaks2 <- c(-Inf,0,Inf)
d2 <- transform(sim(m2,5e2),
z1=cut(y1,breaks=breaks1),
z2=cut(y2,breaks=breaks2))
(g1 <- gkgamma(d2[,3:4]))
## same as
\dontrun{
gkgamma(table(d2[,3:4]))
gkgamma(multinomial(d2[,3:4]))
}
##partial gamma
d2$x <- rbinom(nrow(d2),2,0.5)
gkgamma(z1~z2|x,data=d2)
}
\author{
Klaus K. Holst
}
|
