In debruine/pipeline: Machine-Readable Studies

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

pipeline

The goal of pipeline is to generate and process machine-readable study descriptions.

Installation

You can install the released version of pipeline from GitHub with:

devtools::install_github("scienceverse/pipeline")

Example

Get the file paths to the json file and data. Load the study parameters and data with the pipeline() function; this will run the analyses.

library(pipeline)

# find file paths to data included with this package installation
iat_json_path <- system.file("extdata", "iat.json", package = "pipeline")
iat_data_path <- system.file("extdata", "iat.csv", package = "pipeline")

iat_study <- pipeline(iat_json_path, iat_data_path)

Generate a report. Set results='asis' in the code chunk.

summary(iat_study, "hypotheses", "analyses", "results")

debruine/pipeline documentation built on May 8, 2019, 8:59 a.m.