Modules
Modules are the scripts, codebooks, and infrastructure needed to harmonize a group of related survey items. The core of each module is a set of scripts that format the related survey items. There is one script for every survey source. These scripts include sections for every wave, round, or year within each source. Each section creates two identification variables, one identifying respondents and one identifying the survey round. This enables matching individual respondents across all sources to accurately merge data from multiple modules together. The current modules are listed below. Titles under each module indicate separate series within the module. We also maintain a blank template module so researchers can easily add new variables.
Happiness: Happy Life
Happiness: Satisfaction with Life One Leads
Happiness: Satisfaction with Life as a Whole
Contentment: Perceived Getting Things Wanted
Contentment: Best or Worst Possible Life
Hedonic Affect: Depressed
Hedonic Affect: Everything an Effort
Hedonic Affect: Restless/Bad Sleep
Hedonic Affect: Happy
Hedonic Affect: Lonely/Remote
Hedonic Affect: Enjoying Life
Hedonic Affect: Sad
Hedonic Affect: Apathetic/Unmotivated
Hedonic Affect: Energetic
Hedonic Affect: Anxious
Hedonic Affect: Tired
Hedonic Affect: Engaged/Absorbed
Hedonic Affect: Calm/Peaceful
Hedonic Affect: Bored
Hedonic Affect: Rested
Hedonic Affect: Excited/Interested
Hedonic Affect: Restless/Agitated
Hedonic Affect: Proud Because Complimented
Hedonic Affect: Pleased with Accomplishment
Hedonic Affect: Life Wonderful
Hedonic Affect: Things Going Your Way
Hedonic Affect: Upset Because Criticized
Hedonic Affect: Stressed
Hedonic Affect: Content
Hedonic Affect: Angry
Blogs
Clubhouse
Discord
Facebook
Flickr
Friendster
Google+
Hi5
Instagram
Internet
Live Journal
LinkedIn
Messenger
Mobile Phone
Most Used Source
Myspace
Newspapers
No Social Media
Odnoklassniki
Orkut
Other Social Media
Overall
Pinterest
Podcasts
Radio
Reddit
Signal
Snapchat
Social Media
Sonico
Telegram
Television
TikTok
Tumblr
Twitch
Twitter
Viber
Video Hosting Sites
Vine
Vkontakte
WhatsApp
Windows Live Space
YouTube
Spending on Childcare
Spending on Culture and Arts
Spending on Defence
Spending on Disabilities
Spending on Education
Spending on Environment
Spending on Foreign Aid
Spending on Healthcare
Spending on Homeless
Spending on Law Enforcement
Spending on Pensions
Spending on Poverty
Spending on Science and Technology
Spending on Social Security
Spending on Social Services
Spending on Unemployment
Spending on Welfare
Trust in African Union
Trust in Andean Community
Trust in APEC Forum
Trust in Arab League
Trust in ASEAN
Trust in Banks
Trust in Charities
Trust in Civil Service
Trust in Companies
Trust in Council of the European Union
Trust in Education System
Trust in Electoral Management Body
Trust in European Union
Trust in European Parliament
Trust in European Commission
Trust in European Central Bank
Trust in European Council
Trust in Executive
Trust in Government
Trust in Groups / Movements
Trust in Healthcare System
Trust in Interamerican Development Bank
Trust in International Criminal Court
Trust in International Monetary Fund
Trust in Judiciary
Trust in Latin American Development Bank
Trust in NAFTA
Trust in Ombudsman
Trust in Organisation of African Unity
Trust in Organization of American States
Trust in Parliament
Trust in Police
Trust in Political Parties
Trust in Political System
Trust in Media
Trust in Military
Trust in NATO
Trust in Nongovernmental Organizations
Trust in Religious Institutions
Trust in SAARC
Trust in Scientists
Trust in Southern Common Market
Trust in State Security
Trust in Supreme Audit Institution
Trust in Tax Authorities
Trust in Trade Unions
Trust in United Nations
Trust in United Nations Development Program
Trust in Welfare System
Trust in World Bank
Trust in World Health Organization
Trust in World Trade Organization
Immigrants and Culture
Immigrants Make Country Better
Immigrants Enrich Economy and Culture
Immigrants Threaten Society
Minorities Threaten Society
Migrants Threaten Society
Opinions of Others
Religious Rights
Other Races Disturbing
Other Nationalities Disturbing
Other Religions Disturbing
Equal Opportunities
Women’s Equality
Immigrants’ Equality
How do modules work?
Variables are formatted within the round or wave sections within each source scrip. Variables are renamed for consistency, valid values are re-ordered but not transformed (so all data is conserved), and missing or invalid values are re-coded to match a common framework shared by all modules. After the formatting process are rounds and sources are merged together for each module.
Each module includes a labeling script and a harmonization script. The labeling script applies variable and value labels to every formatted variable within the module. This happens after data from all sources is merged together to avoid repeating the labeling process within each source. Doing it at this point is more efficient because the same formatted variables often appear across sources where the question and answers are the same. The harmonization script creates common variables that combine data from many sources. Usually this is achieved by reducing the diversity of answers to a least common denominator shared by all or most variables. However, since we maintain the original values of all formatted variables it remains possible to easily create additional harmonized variables.
Finally, each module includes a codebook. We generally maintain one main master codebook that includes all variables from all modules. However, when a module is under active development we parse out the relevant section to create a codebook for just that module. Then when development work is complete we recombine the module codebook into the main codebook. This only happens after undertaking quality control checks on all scripts to fix errors and ensure the data matches the module codebook.
Why use modules?
Modules enable multiple individuals or teams to develop different sets of variables simultaneously. This facilitates rapid development and is fundamental to the collaborative approach adopted by HUMAN Surveys. People can share their work with others while also benefiting from the work done by others. The most common approach taken by researchers is to first update or create the module containing their dependent variable. Then researches can focus on updating or adding needed dependent variables only where they have their dependent variables. The scripting framework expands as more people contribute to the modules and nobody needs to repeat the work done by others.
Modules also provide a more manageable framework than having all variables formatted within the same scripts. This was how things started, but scripts became long and cumbersome. It quickly became necessary to separate out different sets of variables. The common tasks of loading, identifying, saving, appending, and merging datasets were also parsed out to a common set of backend system scripts. These are not modified by people developing modules. The modular approach embedded with a common system reduces human error risks because damage can only impact one module and common tasks are not edited.
In addition to all the modules below, we maintain a blank template module that enables researchers to easily add new variables to the framework.