mcguinlu

devtools::install_github("mcguinlu/robvis")
devtools::install_github("mcguinlu/triangulate")
library(dplyr)

# View the example dataset included in the robvis package
# This is what I am guessing your data from the assessments should look like
View(robvis::data_bias_direction)

# Notes on column names:
# d*j = judgement for domain *

mcguinlu

t <- "https://www.everymancinema.com/bristol"

today <- "2021-07-21"

tmp <- read_html(t) %>%
  html_nodes(
    xpath = glue::glue(
      '//div[@data-film-session="{today}"] //*[contains(concat( " ", @class, " " ), concat( " ", "filmTimeItem", " " ))]',
      today = today
    )

mcguinlu

library(shiny)
library(rsvg)
library(DT)
library(rio)

source("functions.R")

template <- read.csv("www/PRISMA.csv",stringsAsFactors = FALSE)

# Define UI for application that draws a histogram

mcguinlu

---
title: "metafor test"
output: html_document
---

```{r setup_main, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)

library(metafor)

mcguinlu

---
title: "metafor test"
output: html_document
---

```{r setup_main, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)

library(metafor)

mcguinlu

library(rtweet)
library(tidyr)
library(dplyr)
library(ggplot2)

rt1 <- search_tweets(
       "#ESMARConf2021", n = 20000, include_rts = TRUE
   )
rt2 <- search_tweets(
       "#ESMARConf", n = 20000, include_rts = TRUE

mcguinlu

all_caps <- function(x) {
  
  x_v <- stringr::str_to_lower(x) %>%
  stringr::str_split(stringr::boundary()) %>%
  unlist()

for (position in 1:nchar(x)) {
  x_v[position] <- paste0("[",stringr::str_to_upper(x_v[position]),x_v[position],"]") 
}
  

mcguinlu

query <- list("[Mm]endelian","[Rr]andomi[sz]ation","[Bb]ias")

# medrxiv ----
# Get local copy of the databases
mx_data <- medrxivr::mx_snapshot() # medrxiv

# Limit to unpublished studies
mx_data_unpublished <- dplyr::filter(mx_data, is.na(published))

# Run search

mcguinlu

devtools::install_github("nealhaddaway/PRISMA2020")
library(PRISMA2020)

# This is the template CSV file, available from the PRISMA2020 repo
# You'll need to edit the numbers in this file to update the image
data <- read.csv("https://raw.githubusercontent.com/nealhaddaway/PRISMA2020/master/inst/extdata/PRISMA.csv",
                 stringsAsFactors = FALSE)

# Set the data as PRISMA data
data <- read_PRISMAdata(data)

mcguinlu

library(shiny)
library(DT)

# Define UI for application that draws a histogram
ui <- fluidPage(
    
    # Application title
    titlePanel("Old Faithful Geyser Data"),
    
    DT::dataTableOutput("mytable")