Measurement

Measurement Bias refers to errors or inaccuracies in the measurement of variables, which can undermine the validity of research outcomes. Causes vary across data types, with

poorly designed questions or respondents’ lacking engagement with the questionnaire leading to response biases and distorted responses in survey data,
challenges of matching observable digital behaviors with theoretical concepts and measurement inconsistencies across platforms affecting digital behavioral data, and
inconsistencies in construct specification or varying measurement standards between different datasets impacting the overall validity of linked data.

AreaMatch

Assessing Geospatial Linking of Incongruent Units

Resquin

Assessing Response Quality and Careless Responding in Multi-Item Scales

ScaleArch

*ZIS R-Tutorials: Basic Analysis for Scale Archiving*

Survey Quality Predictor

A survey quality prediction system for continuous questions used in survey research

TextPrep

Comparing Tools and Workflows for Data Quality in Basic Text Preprocessing with R

ValiText

A Validation Framework for Text-Based Measures of Social Constructs