In antaldaniel/retroharmonize: Ex Post Survey Data Harmonization

Retrospective survey harmonization comes with many challenges, as we have shown in the introduction to this tutorial case study. In this example, we will work with Eurobarometer’s data.

knitr::opts_chunk$set(echo = TRUE)

Please use the development version of retroharmonize:

devtools::install_github("antaldaniel/retroharmonize")

library(retroharmonize)
library(dplyr, quietly = T)       # this is necessary for the example 
library(lubridate)   # easier date conversion
library(stringr)     # You can also use base R string processing functions 
library(purrr)       # functional programing
library(here)        # for finding the project root when working with Rmd files
here::here()

Get the Data

retroharmonize is not associated with Eurobarometer, its creators (Kantar), or its archivists (GESIS). We assume that you have acquired the necessary files from GESIS after carefully reading their terms and that you have placed them on a path that you call gesis_dir. The precise documentation of the data we use can be found in this supporting blogpost. To reproduce this blogpost, you will need ZA5877_v2-0-0.sav, ZA6595_v3-0-0.sav, ZA6861_v1-2-0.sav, ZA7488_v1-0-0.sav, ZA7572_v1-0-0.sav in a directory that you have named gesis_dir.

# Not run in the blogpost. In the repo we have a saved version.
climate_change_files <- c("ZA5877_v2-0-0.sav", "ZA6595_v3-0-0.sav",  "ZA6861_v1-2-0.sav", 
                          "ZA7488_v1-0-0.sav", "ZA7572_v1-0-0.sav")

eb_climate_waves <- read_surveys(
  file.path(gesis_dir, climate_change_files), 
  .f='read_spss')

if (dir.exists("data-raw")) {
  save ( eb_climate_waves,  
         file = here::here("data-raw", "eb_climate_change_waves.rda") )
}

if ( file.exists( here::here("data-raw", "eb_climate_change_waves.rda")) ) {
  load (here::here( "data-raw", "eb_climate_change_waves.rda" ) )
}

The eb_waves nested list contains five surveys imported from SPSS to the survey class of retroharmonize. The survey class is a data.frame that retains important metadata for further harmonization.

document_waves (eb_climate_waves)

Beware of the object sizes. If you work with many surveys, memory-efficient programming becomes imperative. We will be subsetting whenever possible.

Metadata analysis

As noted before, be prepared to work with nested lists. Each imported survey is nested as a data frame in the eb_waves list.

eb_climate_metadata <- lapply ( X = eb_waves, 
                                FUN = retroharmonize::metadata_create )
eb_climate_metadata <- do.call(rbind, eb_climate_metadata)

Metadata: Protocol Variables

Eurobarometer refers to certain metadata elements, like interviewee cooperation level or the date of a survey interview as protocol variables. Let's start here. This will be our template to harmonize more and more aspects of the five surveys (which are, in fact, already harmonizations of about 30 surveys conducted in a single 'wave' in multiple countries.)

```r

select variables of interest from the metadata

eb_protocol_metadata <- eb_climate_metadata %>% filter ( .data$label_orig %in% c("date of interview") | .data$var_name_orig == "rowid") %>% suggest_var_names( survey_program = "eurobarometer" )