odds.ratio | R Documentation |
S3 method for odds ratio
odds.ratio(x, ...) ## S3 method for class 'glm' odds.ratio(x, level = 0.95, ...) ## S3 method for class 'multinom' odds.ratio(x, level = 0.95, ...) ## S3 method for class 'factor' odds.ratio(x, fac, level = 0.95, ...) ## S3 method for class 'table' odds.ratio(x, level = 0.95, ...) ## S3 method for class 'matrix' odds.ratio(x, level = 0.95, ...) ## S3 method for class 'numeric' odds.ratio(x, y, level = 0.95, ...) ## S3 method for class 'odds.ratio' print(x, signif.stars = TRUE, ...)
x |
object from whom odds ratio will be computed |
... |
further arguments passed to or from other methods |
level |
the confidence level required |
fac |
a second factor object |
y |
a second numeric object |
signif.stars |
logical; if |
For models calculated with glm
, x
should have
been calculated with family=binomial
.
p-value are the same as summary(x)$coefficients[,4]
.
Odds ratio could also be obtained with exp(coef(x))
and
confidence intervals with exp(confint(x))
.
For models calculated with multinom
(nnet),
p-value are calculated according to
https://stats.oarc.ucla.edu/r/dae/multinomial-logistic-regression/.
For 2x2 table
, factor
or matrix
, odds.ratio
uses fisher.test
to compute the odds ratio.
Returns a data.frame of class odds.ratio
with odds ratios,
their confidence interval and p-values.
If x
and y
are proportions, odds.ratio
simply
returns the value of the odds ratio, with no confidence interval.
Joseph Larmarange <joseph@larmarange.net>
glm
in the stats package.
multinom
in the nnet package.
fisher.test
in the stats package.
printCoefmat
in the stats package.
data(hdv2003) reg <- glm(cinema ~ sexe + age, data=hdv2003, family=binomial) odds.ratio(reg) odds.ratio(hdv2003$sport, hdv2003$cuisine) odds.ratio(table(hdv2003$sport, hdv2003$cuisine)) M <- matrix(c(759, 360, 518, 363), ncol = 2) odds.ratio(M) odds.ratio(0.26, 0.42)
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