Apply bootstrap to RAM-OP indicators using a classical estimator.
estimate_classic(
x,
w,
statistic = bbw::bootClassic,
indicators = c("demo", "food", "hunger", "adl", "disability", "mental", "dementia",
"health", "oedema", "screening", "income", "wash", "visual", "misc"),
params = get_variables(indicators),
outputColumns = params,
replicates = 399
)
A tibble::tibble()
of boot estimates using bbw::bootClassic()
mean function
Indicators dataset produced by create_op()
with primary sampling
unit (PSU) in column named "psu".
A data frame with primary sampling unit (PSU) in column named "psu" and survey weight (i.e. PSU population) in column named "pop".
A function operating on data in x
. Fixed to
bbw::bootClassic()
function for means.
A character vector of indicator set names to estimate. Indicator set names are "demo", "food", "hunger", "disability", "adl", "mental", "dementia", "health", "income", "wash", "visual", and "misc". Default is all indicator sets.
Parameters (named columns in x
) passed to the function
specified in statistic
. This is equivalent to variables corresponding to
the indicator sets specified in indicators
. The function
get_variables()
is used to specify these variables.
Names of columns in output data frame. This defaults to
values specified in params
.
Number of bootstrap replicates
test <- estimate_classic(
x = indicators.ALL, w = testPSU, replicates = 9
)
test
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