aggregate_impute: Aggregate an imputed dataset

In INBO-BMK/multimput: Using Multiple Imputation to Address Missing Data

Aggregate an imputed dataset

Description

Aggregate an imputed dataset

Usage

aggregate_impute(object, grouping, fun, filter = list(), join)

## S4 method for signature 'ANY'
aggregate_impute(object, grouping, fun, filter = list(), join)

## S4 method for signature 'rawImputed'
aggregate_impute(object, grouping, fun, filter = list(), join)

## S4 method for signature 'aggregatedImputed'
aggregate_impute(object, grouping, fun, filter = list(), join)

Arguments

object	A rawImputed object.
grouping	A vector of variables names to group the aggregation on.
fun	The function to aggregate.
filter	An optional argument to filter the raw dataset before aggregation. Will be passed to dplyr::filter().
join	An optional argument to filter the raw dataset based on a data.frame. A dplyr::semi_join() will be applied with join or each element of join in case join is a list.

Examples

dataset <- generate_data(n_year = 10, n_site = 50, n_run = 1)
dataset$Count[sample(nrow(dataset), 50)] <- NA
model <- lm(Count ~ Year + factor(Period) + factor(Site), data = dataset)
imputed <- impute(data = dataset, model = model)
aggregate_impute(imputed, grouping = c("Year", "Period"), fun = sum)

INBO-BMK/multimput documentation built on Sept. 14, 2023, 6:04 p.m.