Survey Harmonization

Mon, 05 Jul 2021 08:00:00 +0000

We provide retrospecitve, ex post, and ex ante survey harmonization to our partners.

The aim of retrospective survey harmonization is to pool data from pre-existing surveys made with a similar methodology in different points in time and different countries or territories. Ex post survey harmonization is in a way a passive form of pooling research funding because you can utilize information from surveying that were made on somebody else’s expense.

The Arab Barometer surveys do not have a consolidated codebook, but our retroharmonize software created one, and put together data from three years and collected in many countries about various public policy issues.

The aim of ex ante survey harmonization is to maximize the value from future retrospective harmonization; in a way, it is an active form of pooling research funding, because you benefit from money spent on related open governmental and open science survey programs.

In this example we designed a survey representative among music professionals that it can be compared with large-sample, national surveys on living conditions and attitudes, and with occupational groups. Nationally representative surveys do not question enough musicians to allow such specific use; musician only surveys do not allow comparison.

retorhamonize is a peer-reviewed, scientfic statistcal software that allows the programmatic retrospective harmonization of surveys, such as the last 35 years of all Eurobarometer microdata, or all Afrobarometer microdata. Eurobarometer grew out of certain CEE member states’ need for comparable data about their music and audiovisual sectors. We commissioned surveys following ESSNet-Culture guidelines and combined our survey data with open access European microdata-level surveys.

regions solves the problems caused by Europe’s shifting regional boundaries, which have undergone changes in several thousand places over the last twenty years, meaning member states’ and Eurostat’s regional statistics are not comparable over more than two to three years. This software validates and, where possible, changes the regional coding from NUTS1999 until the not yet used NUTS2021, opening up vast, valuable, untapped data sources that can be used for longitudinal analysis or for panel analysis far more precise than what national data alone would allow. It was originally designed in a research project at IVIR in the University of Amsterdam to understand the geographical dynamics of book piracy. Because of the needs this software fills, it had 700 users in the first month after publication. It is particularly useful to re-code old surveys, as regional boundaries are changing in each decade several hundred times in Europe.

retroharmonize R package for survey harmonization

Tue, 25 Aug 2020 00:00:00 +0000

Retrospective data harmonization

The aim of retroharmonize is to provide tools for reproducible retrospective (ex-post) harmonization of datasets that contain variables measuring the same concepts but coded in different ways. Ex-post data harmonization enables better use of existing data and creates new research opportunities. For example, harmonizing data from different countries enables cross-national comparisons, while merging data from different time points makes it possible to track changes over time.

Retrospective data harmonization is associated with challenges including conceptual issues with establishing equivalence and comparability, practical complications of having to standardize the naming and coding of variables, technical difficulties with merging data stored in different formats, and the need to document a large number of data transformations. The retroharmonize package assists with the latter three components, freeing up the capacity of researchers to focus on the first.

Specifically, the retroharmonize package proposes a reproducible workflow, including a new class for storing data together with the harmonized and original metadata, as well as functions for importing data from different formats, harmonizing data and metadata, documenting the harmonization process, and converting between data types. See here for an overview of the functionalities.

The new labelled_spss_survey() class is an extension of haven’s labelled_spss class. It not only preserves variable and value labels and the user-defined missing range, but also gives an identifier, for example, the filename or the wave number, to the vector. Additionally, it enables the preservation – as metadata attributes – of the original variable names, labels, and value codes and labels, from the source data, in addition to the harmonized variable names, labels, and value codes and labels. This way, the harmonized data also contain the pre-harmonization record. The stored original metadata can be used for validation and documentation purposes.

The vignette Working With The labelled_spss_survey Class provides more information about the labelled_spss_survey() class.

In Harmonize Value Labels we discuss the characteristics of the labelled_spss_survey() class and demonstrates the problems that using this class solves.

We also provide three extensive case studies illustrating how the retroharmonize package can be used for ex-post harmonization of data from cross-national surveys:

The creators of retroharmonize are not affiliated with either Afrobarometer, Arab Barometer, Eurobarometer, or the organizations that designs, produces or archives their surveys.

We started building an experimental APIs data is running retroharmonize regularly and improving known statistical data sources. See: Digital Music Observatory, Green Deal Data Observatory, Economy Data Observatory.

Citing the data sources

Our package has been tested on three harmonized survey’s microdata. Because retroharmonize is not affiliated with any of these data sources, to replicate our tutorials or work with the data, you have download the data files from these sources, and you have to cite those sources in your work.

Afrobarometer data: Cite Afrobarometer Arab Barometer data: cite Arab Barometer. Eurobarometer data: The Eurobarometer data Eurobarometer raw data and related documentation (questionnaires, codebooks, etc.) are made available by GESIS, ICPSR and through the Social Science Data Archive networks. You should cite your source, in our examples, we rely on the GESIS data files.

Citing the retroharmonize R package

For main developer and contributors, see the package homepage.

This work can be freely used, modified and distributed under the GPL-3 license:

citation("retroharmonize")
#> 
#> To cite package 'retroharmonize' in publications use:
#> 
#>   Daniel Antal (2021). retroharmonize: Ex Post Survey Data
#>   Harmonization. R package version 0.1.17.
#>   https://retroharmonize.dataobservatory.eu/
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {retroharmonize: Ex Post Survey Data Harmonization},
#>     author = {Daniel Antal},
#>     year = {2021},
#>     doi = {10.5281/zenodo.5006056},
#>     note = {R package version 0.1.17},
#>     url = {https://retroharmonize.dataobservatory.eu/},
#>   }

Contact

For contact information, contributors, see the package homepage.

Code of Conduct

Please note that the retroharmonize project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Click the Cite button above to demo the feature to enable visitors to import publication metadata into their reference management software.

survey harmonization | Open Music Europe