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
|
#' @rdname sensitivity
#' @export
negPredValue <-
function(data, ...){
UseMethod("negPredValue")
}
#' @rdname sensitivity
#' @export
"negPredValue.default" <-
function(data, reference, negative = levels(reference)[2], prevalence = NULL, ...)
{
if(!is.factor(reference) | !is.factor(data))
stop("input data must be a factor")
if(length(unique(c(levels(reference), levels(data)))) != 2)
stop("input data must have the same two levels")
lvls <- levels(data)
if(is.null(prevalence)) prevalence <- mean(reference == lvls[lvls != negative])
sens <- sensitivity(data, reference, lvls[lvls != negative])
spec <- specificity(data, reference, negative)
(spec * (1-prevalence))/(((1-sens)*prevalence) + ((spec)*(1-prevalence)))
}
#' @rdname sensitivity
#' @export
"negPredValue.table" <-
function(data, negative = rownames(data)[-1], prevalence = NULL, ...)
{
## "truth" in columns, predictions in rows
if(!all.equal(nrow(data), ncol(data))) stop("the table must have nrow = ncol")
if(!all.equal(rownames(data), colnames(data))) stop("the table must the same groups in the same order")
if(nrow(data) > 2)
{
tmp <- data
data <- matrix(NA, 2, 2)
colnames(data) <- rownames(data) <- c("pos", "neg")
negCol <- which(colnames(tmp) %in% negative)
posCol <- which(!(colnames(tmp) %in% negative))
data[1, 1] <- sum(tmp[posCol, posCol])
data[1, 2] <- sum(tmp[posCol, negCol])
data[2, 1] <- sum(tmp[negCol, posCol])
data[2, 2] <- sum(tmp[negCol, negCol])
data <- as.table(data)
negative <- "neg"
rm(tmp)
}
positive <- colnames(data)[colnames(data) != negative]
if(is.null(prevalence)) prevalence <- sum(data[, positive])/sum(data)
sens <- sensitivity(data, positive)
spec <- specificity(data, negative)
(spec * (1-prevalence))/(((1-sens)*prevalence) + ((spec)*(1-prevalence)))
}
#' @rdname sensitivity
#' @export
"negPredValue.matrix" <-
function(data, negative = rownames(data)[-1], prevalence = NULL, ...)
{
data <- as.table(data)
negPredValue.table(data, prevalence = prevalence)
}
|
