condense {multitool} | R Documentation |
Summarize multiverse parameters
Description
Summarize multiverse parameters
Usage
condense(.unpacked, .what, .how, .group = NULL, list_cols = TRUE)
Arguments
.unpacked |
|
.what |
a specific column to summarize. This could be a model estimate, a summary statistic, correlation, or any other estimate computed over the multiverse. |
.how |
a named list. The list should contain summary functions (e.g., mean or median) the user would like to compute over the individual estimates from the multiverse |
.group |
an optional variable to group the results. This argument is
passed directly to the |
list_cols |
logical, whether to create list columns for the raw values of any summarized columns. Useful for creating visualizations and tables. Default is TRUE. |
Value
a summarized tibble
containing a column for each summary
method from .how
Examples
library(tidyverse)
library(multitool)
# Simulate some data
the_data <-
data.frame(
id = 1:500,
iv1 = rnorm(500),
iv2 = rnorm(500),
iv3 = rnorm(500),
mod1 = rnorm(500),
mod2 = rnorm(500),
mod3 = rnorm(500),
cov1 = rnorm(500),
cov2 = rnorm(500),
dv1 = rnorm(500),
dv2 = rnorm(500),
include1 = rbinom(500, size = 1, prob = .1),
include2 = sample(1:3, size = 500, replace = TRUE),
include3 = rnorm(500)
)
# Decision pipeline
full_pipeline <-
the_data |>
add_filters(include1 == 0,include2 != 3,include2 != 2,scale(include3) > -2.5) |>
add_variables("ivs", iv1, iv2, iv3) |>
add_variables("dvs", dv1, dv2) |>
add_variables("mods", starts_with("mod")) |>
add_model("linear_model", lm({dvs} ~ {ivs} * {mods} + cov1))
pipeline_grid <- expand_decisions(full_pipeline)
# Run the whole multiverse
the_multiverse <- run_multiverse(pipeline_grid[1:10,])
# Reveal and condense
the_multiverse |>
reveal_model_parameters() |>
filter(str_detect(parameter, "iv")) |>
condense(coefficient, list(mean = mean, median = median))
[Package multitool version 0.1.4 Index]