In TomHardwicke/ReproReports: Build reports for reproducibility assignments

[TEXT IN SQUARE BRACKETS IS HERE FOR GUIDANCE. PLEASE DELETE TEXT IN SQUARE BRACKETS BEFORE KNITTING THE FINAL REPORT]

Report Details

[PILOT/COPILOT ENTER RELEVANT REPORT DETAILS HERE]

articleID <- NA # insert the article ID code here e.g., "10-3-2015"
reportType <- NA # specify whether this is the 'pilot' report or 'copilot' report
pilotNames <- NA # insert the pilot's name here e.g., "Tom Hardwicke".
copilotNames <- NA # # insert the co-pilot's name here e.g., "Michael Frank".
pilotTTC <- NA # insert the pilot's estimated time to complete (in minutes, it is fine to approximate) e.g., 120
copilotTTC <- NA # insert the co-pilot's estimated time to complete (in minutes, it is fine to approximate) e.g., 120
pilotStartDate <- NA # insert the piloting start date in US format e.g., as.Date("01/25/18", format = "%m/%d/%y")
copilotStartDate <- NA # insert the co-piloting start date in US format e.g., as.Date("01/25/18", format = "%m/%d/%y")
completionDate <- NA # insert the date of final report completion in US format e.g., as.Date("01/25/18", format = "%m/%d/%y")

---

Methods summary:

[PILOT/COPILOT write a brief summary of the methods underlying the target outcomes written in your own words]

---

Target outcomes:

[PILOT copy and paste the exact target outcomes as written in in targetOutcomes.md]

---

[PILOT/COPILOT DO NOT CHANGE THE CODE IN THE CHUNK BELOW]

# sets up some formatting options for the R Markdown document
knitr::opts_chunk$set(echo=TRUE, warning=FALSE, message=FALSE)

Step 1: Load packages and prepare report object

[PILOT/COPILOT Some useful packages are being loaded below. You can add any additional ones you might need too.]

# load packages
library(tidyverse) # for data munging
library(knitr) # for kable table formating
library(haven) # import and export 'SPSS', 'Stata' and 'SAS' Files
library(readxl) # import excel files
library(ReproReports) # custom reporting functions

[PILOT/COPILOT DO NOT MAKE CHANGES TO THE CODE CHUNK BELOW]

# Prepare report object. This will be updated automatically by the reproCheck function each time values are compared
reportObject <- data.frame(dummyRow = TRUE, reportedValue = NA, obtainedValue = NA, valueType = NA, percentageError = NA, comparisonOutcome = NA, eyeballCheck = NA)

Step 2: Load data

Step 3: Tidy data

Step 4: Run analysis

Pre-processing

Descriptive statistics

Inferential statistics

Step 5: Conclusion

[Please include a text summary describing your findings. If this reproducibility check was a failure, you should note any suggestions as to what you think the likely cause(s) might be.]

[PILOT/COPILOT DOD NOT EDIT THE CODE CHUNK BELOW]

reportObject <- reportObject %>%
  filter(dummyRow == FALSE) %>% # remove the dummy row
  select(-dummyRow) %>% # remove dummy row designation
  mutate(articleID = articleID) %>% # add variables to report 
  select(articleID, everything()) # make articleID first column

# decide on final outcome
if(any(reportObject$comparisonOutcome %in% c("MAJOR_ERROR", "DECISION_ERROR"))){
  finalOutcome <- "Failure"
}else{
  finalOutcome <- "Success"
}

# collate report extra details
reportExtras <- data.frame(articleID, pilotNames, copilotNames, pilotTTC, copilotTTC, pilotStartDate, copilotStartDate, completionDate, finalOutcome)

# save report objects
if(reportType == "pilot"){
  write_csv(reportObject, "pilotReportDetailed.csv")
  write_csv(reportExtras, "pilotReportExtras.csv")
}

if(reportType == "copilot"){
  write_csv(reportObject, "copilotReportDetailed.csv")
  write_csv(reportExtras, "copilotReportExtras.csv")
}

Session information

[This function will output information about the package versions used in this report:]

devtools::session_info()

TomHardwicke/ReproReports documentation built on Oct. 31, 2019, 12:15 a.m.