binary_to_individual: Generate individual-level binary outcome data from an...

In baggr: Bayesian Aggregate Treatment Effects

Generate individual-level binary outcome data from an aggregate statistics

Description

This is a helper function that is typically used automatically by some of baggr functions, such as when running model="logit" in baggr, when summary-level data are supplied.

Usage

binary_to_individual(
  data,
  group = "group",
  covariates = c(),
  rename_group = TRUE
)

Arguments

data	A data frame with columns a, c and b/n1, d/n2. (You can also use ai, ci, n1i, n2i instead.)
group	Column name storing group
covariates	Column names in data that contain group-level variables to retain when expanding into individual-level data.frame
rename_group	If TRUE (default), this will rename the grouping variable to "group", making it easier to work with baggr See vignette("baggr_binary") for an example of use and notation details.

Value

A data frame with columns group, outcome and treatment.

See Also

prepare_ma uses this function

Examples

df_yusuf <- read.table(text="
  trial        a n1i  c n2i
  Balcon      14  56 15  58
  Clausen     18  66 19  64
  Multicentre 15 100 12  95
  Barber      10  52 12  47
  Norris      21 226 24 228
  Kahler       3  38  6  31
  Ledwich      2  20  3  20
  ", header=TRUE)
bti <- binary_to_individual(df_yusuf, group = "trial")
head(bti)
# to go back to summary-level data
prepare_ma(bti, effect = "logOR")
# the last operation is equivalent to simply doing
prepare_ma(df_yusuf, group="trial", effect="logOR")

baggr documentation built on March 31, 2023, 10:02 p.m.