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gsedread

The goal of gsedread is to read validation data of the project Global Scales for Early Development (GSED).

Installation

Install the gsedread package from GitHub as follows:

install.packages("remotes")
remotes::install_github("d-score/gsedread")

There is no CRAN version.

Example

You need access to the WHO SharePoint site and sync the data to a local OneDrive. In the file .Renviron in your home directory add a line specifying the location of your synced OneDrive, e.g.,

ONEDRIVE_GSED='/Users/username/Library/CloudStorage/OneDrive-Sharedlibraries-WorldHealthOrganization/CAVALLERA, Vanessa - GSED Validation 2021_phase I'

After setting the environmental variable ONEDRIVE_GSED, restart R, and manually check whether you are able to read the OneDrive directory.

dir(Sys.getenv("ONEDRIVE_GSED"))
#>  [1] "Bangladesh Validation"                             
#>  [2] "Baseline Analysis - OLD - NOV 2021"                
#>  [3] "DIF_country.png"                                   
#>  [4] "Final Phase 1 Data - May 10th 2022"                
#>  [5] "GSED Final Collated Phase 1 Data Files 18_05_22"   
#>  [6] "GSED PHASE 1 DATA COLLECTED LOG"                   
#>  [7] "GSED_data_quality_1_output_LF_TEST.csv"            
#>  [8] "GSED_data_quality_1_output.csv"                    
#>  [9] "GSED_phase1_merged_11_11_21.csv"                   
#> [10] "interim DAZ values combined.csv"                   
#> [11] "Interim validation data_phase I_May2021"           
#> [12] "Master_data_dictionary_MAIN_v0.9.1_2021.04.22.xlsx"
#> [13] "Pakistan Validation"                               
#> [14] "Pemba Validation"                                  
#> [15] "QUALITATIVE DATA PHASE 1 MAY 2022"                 
#> [16] "Rplot.pdf"                                         
#> [17] "Stop rule change exploration"                      
#> [18] "t1.Rds"

The following commands reads all SF data from GSED Final Collated Phase 1 Data Files 18_05_22 directory and returns a tibble with one record per administration.

library(gsedread)
data <- read_sf()
dim(data)
#> [1] 6228  160

Count the number of records per file:

table(data$file)
#> 
#>                ban_sf_2021_11_03 ban_sf_new_enrollment_17_05_2022 
#>                             1421                               72 
#>     ban_sf_predictive_17_05_2022                pak_sf_2022_05_17 
#>                              473                             1761 
#> pak_sf_new_enrollment_2022_05_17     pak_sf_predictive_2022_05_17 
#>                               72                              459 
#>                tza_sf_2021_11_01 tza_sf_new_enrollment_10_05_2022 
#>                             1427                               74 
#>     tza_sf_predictive_10_05_2022 
#>                              469

Process variable names user-friendly alternative:

rename_vector(colnames(data)[c(1:3, 19, 21:25)], lexout = "gsed2", trim = "Ma_SF_")
#> [1] "file"      "gsed_id"   "parent_id" "date"      "gpalac001" "gpacgc002"
#> [7] "gpafmc003" "gpasec004" "gpamoc005"

Operations

The package reads and processes GSED data. It does not store data. The read_sf() and read_lf() functions takes the following actions:

  1. Constructs the paths to the files OneDrive sync file;
  2. Reads all specified datasets in a list;
  3. Internally specifies the desired format for each column;
  4. Specifies the available date and data-time formats per file;
  5. Recodes empty, NA, -8888, -8,888.00 and -9999 values as NA;
  6. Repairs problems with mixed data-time formats in the adaptive Pakistan data;
  7. Stacks the datasets to one tibble and adds columns file and adm;
  8. Removes records without a GSED_ID.

Item renaming with rename_variables() relies on the item translation table at https://github.com/D-score/gsedread/blob/main/inst/extdata/itemnames_translate.tsv.