odds.ratio: Odds Ratio

odds.ratioR Documentation

Odds Ratio

Description

S3 method for odds ratio

Usage

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, ...)

Arguments

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 TRUE, p-values are encoded visually as 'significance stars'

Details

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.

Value

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.

Author(s)

Joseph Larmarange <joseph@larmarange.net>

See Also

glm in the stats package.

multinom in the nnet package.

fisher.test in the stats package.

printCoefmat in the stats package.

Examples

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)

questionr documentation built on Feb. 16, 2023, 10:14 p.m.