Quantitative Variable Distributions: Multi Site, Anomaly Detection, Cross-Sectional Analysis
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Abstract
This check provides raw data and visualizations to aid a user in evaluating whether the distribution of quantitative variables aligns with clinical expectations. It can summarize the distribution of a quantitative variable (like lab result values) or patient counts (like number of patients with an outpatient visit).
How to Access This Check
- You may access the module’s R package in GitHub.
Or, run in R
install_github('ssdqa/https://github.com/ssdqa/quantvariabledistribution')
- Using the provided vignettes on GitHub or help in R, follow parameter input instructions for “Multi Site”, “Anomaly Detection”, “Cross-Sectional” requirements.
Check Output
Visualization Output
This check outputs a radial lolipop chart displaying the Kullback-Liebler divergence value at each site for each value type included in the analysis. This represents how different the distribution of values at the site is from the overall distribution across all sites.
Raw Output
This check produces a raw data output containing 4 columns:
| Column | Data Type | Definition |
|---|---|---|
site |
character | the name of the site being targeted OR “combined” if multiple sites were provided |
value_type |
character | the type of value being measured |
kl |
numeric | the Kullback-Leibler divergence value between the site’s value distrbution and the overall, all-site distribution |
output_function |
character | a string indicating the type of visualization that should be generated by qvd_output |
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This research was made possible through the generous support of the Patient-Centered Outcomes Research Institute .
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Except where otherwised noted, this item's license is described as a CC-BY Attribution 4.0 License.