In softloud/metasim: Simulate Meta-Analytic Data

knitr::opts_chunk$set(echo = TRUE)

# packages
library(tidyverse)

n_t for treatment or case group n_c for control or placebo group _d for the numeric (double) form

pinheiro_data <- tibble(
  study = c("Catarino", "Dusse", "He", "Schjetlein", "Terao", "Bellart", "Heilmann"),
  year = c(2008, 2003, 1997, 1997, 1991, 1998, 2007),
  n_t = c(44, 43, 30, 200, 13, 12, 111),
  m_t = c(448.5, 1263.8, 315.0, 1545.0, 347.87, 2090.0, 1623.60),
  s_t = list(
    iqr = c(313.0, 1091.3), 
    sd = 411.9, 
    range = c(145.0, 1150), 
    sd = 849.5, 
    sd = 460.5,
    iqr = 1800.0,
    iqr = 932.9),
  n_c = c(42, 28, 24, 97, 80, 65, 33),
  m_c = c(538.2, 1146.6, 183.0, 1390.0, 221.52, 545.0, 1149.0),
  s_c = list(
    iqr = c(391.2, 822.8),
    sd = 311.2,
    range = c(110.0, 340.0),
    sd = 550.0,
    sd = 179.9,
    iqr = 225.0,
    iqr = 456.0
  ),
  centre = c("median", "mean", "median", "mean", "mean", "median", "median"),
  spread = c("iqr", "sd", "range", "sd", "sd", "iqr", "iqr")) %>% 
  mutate(
    s_t_d = map_dbl(s_t, .f = function(s) {
      if (length(s) == 2) return(s[2] - s[1]) else return(s)
    }),
    s_c_d = map_dbl(s_c, .f = function(s) {
      if (length(s) == 2) return(s[2] - s[1]) else return(s)
    }) 
  )

# take a look
pinheiro_data %>% knitr::kable()

write data to lazy load datasets

devtools::use_data(pinheiro_data, overwrite = TRUE)

softloud/metasim documentation built on July 15, 2019, 8:02 p.m.