Notation Used in the DGM: Simulation Data for Digital Health Measure Validation

5.5 KB of simulated data from a study evaluating methods for validating sensor-based digital health technologies. The dataset, authored by Simon Turner and last updated in May 2026, compares statistical techniques like Pearson Correlation Coefficient and Confirmatory Factor Analysis. It was created to address challenges in validating novel digital measures when comparable reference units are unavailable.

Use Cases

• Comparing Pearson Correlation Coefficient and Confirmatory Factor Analysis methods based on the described simulation of latent physical ability traits.
• Evaluating the stability and bias of validation metrics based on simulated step count and self-reported physical activity data.
• Assessing the impact of sample size on analytical validation results based on the study's findings.
• Investigating the use of multiple reference measures in regression models based on the description of linear regression analyses.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Openly licensed under CC-BY-4.0, allowing for broad reuse and sharing.
• Description provides a clear methodological context for the simulation study.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is simulated, not observational, which may limit real-world generalizability.

Provenance

Source

Simon Turner via figshare

Collection Method

Simulated data generated for a methodological study.

Freshness

Last updated 2026-05-13 18:00:40; freshness should be verified.