In fmmattioni/metabolic: Datasets and Functions for Reproducing Meta-Analyses

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  message = FALSE,
  warning = FALSE
)

## prepare data dictionary
library(metabolic)
library(kableExtra)

doc_metabolic_meta <- Rd2roxygen::parse_file(here::here("man/metabolic_meta.Rd"))

data_descriptions <- doc_metabolic_meta$format %>% 
  stringr::str_split(pattern = "\\\\") %>% 
  unlist(recursive = FALSE) %>% 
  dplyr::as_tibble() %>% 
  tail(-2) %>% 
  dplyr::mutate(value = stringr::str_remove(value, pattern = "item\\{(.*?)\\}"),
         value = stringr::str_remove(value, pattern = "\\{|\\}"),
         value = stringr::str_remove(value, pattern = "\\}\n")) %>% 
  dplyr::rename(description = value)

data_dictionary <- metabolic_meta %>% 
  names() %>% 
  tibble::enframe(name = NULL, value = "column") %>% 
  dplyr::bind_cols(data_descriptions)

``{block, type = 'rmdinfo'} Themetabolic_meta` dataset displays the "processed" data from the data extracted from each study. Here, the calculation of the difference in means and of the standard deviation of the mean between pre- and post-training are already calculated. This dataset is used internally to reproduce the meta-analysis results.

Please, refer to the Introduction to metabolic vignette for a walk-through.

## Data download

In case you are not familiar with `R` or just would like to download this dataset, you can choose to download it as a `.xlsx` file.

```r
library(downloadthis)

list("metabolic_meta" = metabolic::metabolic_meta, "data dictionary" = data_dictionary) %>% 
  download_this(
    .data = ., 
    output_name = "metabolic_meta dataset from the {metabolic} package", 
    output_extension = ".xlsx", 
    button_label = "Download data as .xlsx", 
    button_type = "warning"
  )

Data dictionary

data_dictionary %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover"))

fmmattioni/metabolic documentation built on Oct. 17, 2023, 2:41 a.m.