Convert binomial data to bernoulli data

Convert binomial data to bernoulli data by expanding dataset.

binomial_to_bernoulli_data(
  data.,
  y,
  size,
  type = c("rest", "total"),
  response_name = "response",
  rest_name = NULL
)

Arguments

data.

A dataframe

y

Column with 'successes' in binomial distribution y~bin(size, p)

size

Column with 'failures', i.e. size-y or 'total', i.e. size.

type

Whether size is rest (i.e. 'failures') or 'total'

response_name

Name of response variable in output dataset.

rest_name

Name of 'failures' in column response_name.

Examples

dat <- budworm
dat <- dat[dat$dose %in% c(1,2), ]
dat$ntotal <- 5
dat
#>      sex dose ndead ntotal
#> 1   male    1     1      5
#> 2   male    2     4      5
#> 7 female    1     0      5
#> 8 female    2     2      5
dat.a <- dat |>
  binomial_to_bernoulli_data(ndead, ntotal, type="total")
dat.b <- dat |>
  dplyr::mutate(nalive=ntotal-ndead) |> dplyr::select(-ntotal) |>
  binomial_to_bernoulli_data(ndead, nalive, type="rest")

m0 <- glm(cbind(ndead, ntotal-ndead) ~ dose + sex, data=dat, family=binomial())
m1 <- glm(ndead / ntotal ~ dose + sex, data=dat, weight=ntotal, family=binomial())
ma <- glm(response ~ dose + sex, data=dat.a, family=binomial())
mb <- glm(response ~ dose + sex, data=dat.b, family=binomial())

dat.a$response
#>  [1] ndead     not_ndead not_ndead not_ndead not_ndead ndead     ndead    
#>  [8] ndead     ndead     not_ndead not_ndead not_ndead not_ndead not_ndead
#> [15] not_ndead ndead     ndead     not_ndead not_ndead not_ndead
#> Levels: not_ndead ndead
dat.b$response ## Not same and therefore the following do not match
#>  [1] ndead  nalive nalive nalive nalive ndead  ndead  ndead  ndead  nalive
#> [11] nalive nalive nalive nalive nalive ndead  ndead  nalive nalive nalive
#> Levels: nalive ndead

all.equal(coef(m0), coef(ma))
#> [1] TRUE
all.equal(coef(m0), coef(mb))
#> [1] TRUE
all.equal(coef(m1), coef(ma))
#> [1] TRUE
all.equal(coef(m1), coef(mb))
#> [1] TRUE