statcodelists: Use Standardized Statistical Codelists
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.
Citations and related work
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.