University of Michigan - Measuring Total Data Quality 

Welcome to Course 2!

Measuring Validity for Designed Data

Example 1: Performing CFA and Examining Measurement Invariance in R

Approaches and Considerations for Measuring Quality for Gathered Data

Measuring Validity for Gathered Data

Measuring Data Origin Quality for Designed Data

Examples: Computing Measures of Data Origin Quality for Designed Data in R

Measuring Data Origin Quality for Gathered Data

Example 4: Measuring Validity and Data Origin Quality for Gathered Data

Course Syllabus

Course Pre-Survey

Example 1: Output file and .csv file

Example 2: A tutorial on estimating 'true-score' multitrait-multimethod models with lavaan in R

Output file for the next Examples video

Case Study: Measuring the Quality of Cause-of-Death Data at the CDC

Interpreting Validity Metrics

Interpreting Data Origin Quality Metrics

Measuring Processing Quality for Designed Data

Example: Computing Processing Metrics with Real Data and Code

Measuring Processing Quality for Gathered Data

Example: Computing Processing Metrics for Gathered Data

Measuring Data Access Quality for Designed Data

Example: Computing Access Metrics with Read Data and Code

Measuring Data Access Quality for Gathered Data

Case Study: Measuring Data Access Quality in Gathered Twitter Data

Case study article: Hino and Fahey 2019

Interpreting Processing Metrics

Interpreting Access Metrics

Measuring Data Source Quality for Designed Data

Example: Computing Data Source Metrics with Real Data and Code

Measuring Data Source Quality for Gathered Data

Example: Computing Data Source Quality Metrics with Real Data and Code

Measuring Threats to Data Source Quality: Designed Data

Example: Computing Data Missingness Metrics with Real Data and Code

Measuring Data Missingness for Gathered Data

Example: Computing Data Missingness for Gathered Data

Link to R software and Examples on GitHub (from previous lecture)

Interpreting Data Source Quality Metrics

Interpreting Data Missingness Metrics

Measuring the Quality of an Analysis of Designed Data

Example: Computing Measures of Data Analysis Quality for Designed Data in R

Measuring the Quality of an Analysis of Gathered Data

Example: Computing Metrics for Quality of Models of Gathered Data

Suggested readings from the previous lecture

The Aequitas Bias Toolkit for Auditing Machine Learning Models

Course Conclusion

References for Measuring Total Data Quality

Course Post-Survey

Examining Analysis Quality Metrics and Interpreting Output