SURVEY DATA INTEGRATION

I am particularly passionate about this topic, which is also the subject of my PhD thesis.

Survey data integration refers to the combination of data coming from different surveys or sources. Traditional probability sample surveys are suffering from low response rate and can be prohibitively expensive. New sources, including volunteer web surveys and big data (e.g. social media, google trends, sensors etc.) are emerging. Thus, an interesting field of research is the integration of traditional and non-traditional sources in order augment the information available, reducing the cost of the analysis.

I'm collaborating with two research groups, considering both web-surveys and social media data.

Preliminary results have been presented at international conferences and more papers are in preparation.

Check my publication and coference presentation list for more insight on my work!

Poster presented in Paris at the Bayesian for Social Science Workshop

Selected research outcomes:

Salvatore C., (2023). Inference with non-probability samples and survey data integration: a science mapping study. Metron, https://doi.org/10.1007/s40300-023-00243-6
Salvatore C., Biffignandi S., Sakshaug J., Wiśniowski A., Struminskaya B., (2023). Bayesian integration of probability and non-probability samples for logistic regression. Journal of Survey Statistics and Methodology, https://doi.org/10.1093/jssam/smad041 - Supplemented with a Shiny App
Salvatore C., Biffignandi S., Bianchi A., (2023). Augmenting Business Statistics Information by Combining Traditional Data with Textual Data: A Composite Indicator Approach, Metron

Collaboration with two research groups:

Integrating probability and nonprobability samples for analytic inference: Silvia Biffignandi, Joe Sakshaug, Arek Wiśniowski and Bella Struminskaya
Augmenting traditional data with digital trace data: Silvia Biffignandi and Annamaria Bianchi

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