Ever wondered about the reliability of interviews in your surveys? RISSK utilizes machine learning algorithms to generate a risk score from your Survey Solutions export files. This score indicates the likelihood of unwanted interviewer behaviour in individual interviews. It is a valuable tool to prioritize suspicious interviews for verification exercises such as back-checking or audio audits.
- Comprehensive. Checks many features in paradata and microdata.
- Accessible output. Score easy to interpret, range from 0-100.
- Generic. No adjustments or survey specifics required.
- Flexible. Easily integratable into existing quality monitoring systems.
- Easy to set-up and run. Only requires exports files + a few lines of command.
- Platform independent. runs on Windows, Mac, Linux.
- Preserves data privacy. Runs locally, no need to share/upload data.
- Adjustable. Advanced users can tailor composition of URS.
- Free and open source. Public repository on WorldBank GitHub.
Curious to find out more? Want to start using it? Dive in here: