The code pasted below from ResourceSelection::hoslem.test performs a Hosmer and Lemeshow goodness of fit test. While investigating why the output that does not agree exactly with that performed by another software (Stata), I found that the difference relates to use of default R argument for the quantile function (type=7). I would like to use this function with a different default for calculation of quantiles (type=6).
FWIW, the reference to the 9 possible methods used by R can be found at:
https://www.amherst.edu/media/view/129116/original/Sample+Quantiles.pdf
The Stata manual for pctile refers to a default method and an 'altdef' method. I found it difficult to map these two methods to corresponding R types.
However,
hoslem.test(yhat, y, type=6)
Produces:
> hl <- hoslem.test(y, yhat, type=6)
Error in hoslem.test(y, yhat, type = 6) : unused argument (type = 6)
Is there a way to run the function below with a non-default argument for the quantile function?
Ie. allows the following line adding ', type=6':
qq <- unique(quantile(yhat, probs = seq(0, 1, 1/g), type=6))
The function in question is:
> ResourceSelection::hoslem.test
function (x, y, g = 10)
{
DNAME <- paste(deparse(substitute(x)), deparse(substitute(y)),
sep = ", ")
METHOD <- "Hosmer and Lemeshow goodness of fit (GOF) test"
yhat <- y
y <- x
qq <- unique(quantile(yhat, probs = seq(0, 1, 1/g)))
cutyhat <- cut(yhat, breaks = qq, include.lowest = TRUE)
observed <- xtabs(cbind(y0 = 1 - y, y1 = y) ~ cutyhat)
expected <- xtabs(cbind(yhat0 = 1 - yhat, yhat1 = yhat) ~
cutyhat)
chisq <- sum((observed - expected)^2/expected)
PVAL = 1 - pchisq(chisq, g - 2)
PARAMETER <- g - 2
names(chisq) <- "X-squared"
names(PARAMETER) <- "df"
structure(list(statistic = chisq, parameter = PARAMETER,
p.value = PVAL, method = METHOD, data.name = DNAME, observed = observed,
expected = expected), class = "htest")
}
3 个答案:
答案 0 :(得分：2)
我们可以修改各种功能。看一下函数的主体
as.list(body(hoslem.test))
看到我们想要修改的元素是正文中的第6个元素
[[1]]
`{`
[[2]]
DNAME <- paste(deparse(substitute(x)), deparse(substitute(y)),
sep = ", ")
[[3]]
METHOD <- "Hosmer and Lemeshow goodness of fit (GOF) test"
[[4]]
yhat <- y
[[5]]
y <- x
[[6]]
qq <- unique(quantile(yhat, probs = seq(0, 1, 1/g)))
将第6个元素修改为您想要的内容
body(hoslem.test)[[6]] = substitute(qq <- unique(quantile(yhat,
probs = seq(0, 1, 1/g), type = 6)))
答案 1 :(得分：1)
The easiest way would be to reenter the function as your own:
myhoslem.test<-function(x, y, g = 10, mytype = 6){
DNAME <- paste(deparse(substitute(x)), deparse(substitute(y)),
sep = ", ")
METHOD <- "Hosmer and Lemeshow goodness of fit (GOF) test"
yhat <- y
y <- x
qq <- unique(quantile(yhat, probs = seq(0, 1, 1/g), type = mytype))
cutyhat <- cut(yhat, breaks = qq, include.lowest = TRUE)
observed <- xtabs(cbind(y0 = 1 - y, y1 = y) ~ cutyhat)
expected <- xtabs(cbind(yhat0 = 1 - yhat, yhat1 = yhat) ~
cutyhat)
chisq <- sum((observed - expected)^2/expected)
PVAL = 1 - pchisq(chisq, g - 2)
PARAMETER <- g - 2
names(chisq) <- "X-squared"
names(PARAMETER) <- "df"
structure(list(statistic = chisq, parameter = PARAMETER,
p.value = PVAL, method = METHOD, data.name = DNAME, observed = observed,
expected = expected), class = "htest")
}
The key change here is :
qq <- unique(quantile(yhat, probs = seq(0, 1, 1/g), type = mytype))
and allowing mytype as a argument to the function with default as 6
答案 2 :(得分：0)
这两个答案提示了一个包装函数，可以灵活地修改hoslem.test
myhoslem.test<-function(x, y, g = 10, mytype = 6){
body(hoslem.test)[[6]] = substitute(qq <- unique(quantile(yhat,
probs = seq(0, 1, 1/g), type = mytype)))
hoslem.test(x,y, g=10)
}