Marta Kołczyńska

Sociology • Social Science Data & Methods

Age distributions in samples from cross-national survey projects

Cross-national survey projects conduct surveys on representative samples of adult populations. How do the distributions of respondents’ age vary across surveys carried out in the same country in different years and different projects? Like in a couple of previous posts (here, here and here) I use data from the Survey Data Recycling dataset (SDR) version 1, which includes selected harmonized variables from 22 cross-national survey projects. SDR only includes surveys that claim to have samples representative for adult populations.

Reliability of survey estimates: Participation in demonstrations

Data Differences within country-years Differences by groups Gender Age Urban/rural residence Education Sampling scheme The growth in cross-national survey projects in the last decades leads to situations when two or more surveys are carried out in the same country and the same year but in different projects, and contain overlapping sets of survey questions. Assuming that the surveys are based on representative samples - a claim that major cross-national survey projects typically make - it could be expected that estimates from surveys carried out in the same country and year are reasonably close.

tidytext analysis of TED talks

Setup tidy TED talks Applause, LOL Sentiment This year I spent two weeks of the summer attending the Summer Institute for Computational Social Science Parter Site (SICSS) in Tvärminne and Helsinki, Finland, organized by Matti Nelimarkka from Aalto University and the University of Helsinki, assisted by two TAs: Juho Pääkkönen and Pihla Toivanen from the University of Helsinki. I highly recommend it to anyone with background in the social sciences and interested in computer and data sciences, or the other way around!

Validating survey data: Educational attainment in SDR and the OECD

Educational attainment data OECD data SDR data Cleaning and merging SDR and OECD data Results The curious case of ISSP Switzerland Conclusion Appendix with Przemek Powałko General population surveys with representative samples should have a similar education structure as shown by data from administrative sources, especially if survey weights are used. In this post we compare sample aggregates from 15 cross-national survey projects (including the European Social Survey, the World Values Survey and the European Values Study, and others) from the Survey Data Recycling database with educational attainment statistics from the OECD.

Dot plot challenge: Voting gender gaps in Europe

Getting and reshaping the data The Dot Plot The August edition of the Storytelling with Data challenge #SWDchallenge stars the dot plot. Here is a simple plot of the gender gap in voting in national elections using the most recent 8th Round of the European Social Survey, ESS. Getting and reshaping the data library(essurvey) # getting European Social Survey data library(tidyverse) # data cleaning and reshaping library(countrycode) # converting country codes to names library(ggplot2) # plots With the essurvey package the ESS data can be downloaded directly to R.

Shiny app for exploring harmonized cross-national survey data (SDR v.1.0)

Instructions References  In the previous post I wrote about downloading and exploring the Survey Data Recycling (SDR), version 1 dataset, which consists of selected harmonized variables from 22 survey projects, 1966-2013. The SDR project will develop a website for browsing, subsetting, downloading, and visualizing data from the SDR project. This website is currently under construction. Meanwhile, I made a Shiny app with basic functionalities of the future on-line browsing and subsetting tool (also serves as its mock-up): https://mkolczynska.

Exploring the dataset of survey datasets: Survey Data Recycling version 1

Introduction Downloading the SDR data Exploring SDR: availability of variables by project Exploring SDR: availability of variables with different formulations Identifying surveys containing selected variables Subsetting the Master File Country coverage plot Combining data from different survey projects creates new opportunities for research, alas, at the cost of increased volume (obviously) and complexity of the data. The Survey Data Recycling project created a dataset with data from 22 international survey projects.

ISA World Congress 2018: Analysis of tweets

Getting data from Twitter Tweets over time Text analysis Tweets by ISA Resesarch Committee The International Sociological Association 19th World Congress of Sociology in Toronto (15-21 July) has received quite some Twitter coverage. Waiting to board the flight back to Warsaw, I wanted to take a look at these Twitter data and apply the newly acquired skills in text analysis (thanks to the Summer Institute for Computational Social Science, SICSS, Partner Site in Tvärminne and Helsinki, Finland).

Late start

How it all started Step 1. R Step 2. On-line resources Step 3. Done is better than perfect References This blog is going to be mostly about my adventures with R, primarily using survey data, and usually somewhat related to my social science interests; for the fun of it, to share code and hopefully get feedback. How it all started General law of academia: The capacity for generating ideas is greater than the capacity of developing ideas into papers.