Quantitative Variable Distributions: Single Site, Anomaly Detection, Longitudinal Analysis
| dc.contributor | Patient-Centered Outcomes Research Institute |
| dc.contributor.author | PEDSnet |
| dc.contributor.author | Wieand, Kaleigh |
| dc.contributor.author | Dickinson, Kimberley |
| dc.contributor.other | PEDSnet Data Coordinating Center |
| dc.date.accessioned | 2025-08-05T18:11:36Z |
| dc.date.created | 2025-07-30 |
| dc.description.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). |
| dc.description.abstract | #### How to Access This Check 1. You may access the module's R package in [GitHub](https://github.com/ssdqa/https://github.com/ssdqa/quantvariabledistribution).<br> Or, run in R ```{r} install_github('ssdqa/https://github.com/ssdqa/quantvariabledistribution') ``` 2. Using the provided vignettes on GitHub or help in R, follow parameter input instructions for "Single Site", "Anomaly Detection", "Longitudinal" requirements. |
| dc.identifier.uri | https://hdl.handle.net/20.500.14642/1168 |
| dc.publisher | PEDSnet |
| dc.relation.uri | https://github.com/ssdqa/quantvariabledistribution |
| dc.rights | a CC-BY Attribution 4.0 License. |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0 |
| dc.subject | Plausibility |
| dc.subject | Line Graph |
| dc.subject | Event-Level Analysis |
| dc.subject | Clinical Data Distributions |
| dc.subject | Clinical Consistency |
| dc.subject | Selection Error or Bias Detection |
| dc.subject | Information Density |
| dc.title | Quantitative Variable Distributions: Single Site, Anomaly Detection, Longitudinal Analysis |
| dspace.entity.type | DQCheck |
| local.description.raw | This check produces a raw data output containing 10 columns: <br> |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| |`outlier_type`|character|a string indicating whether the outlier is in the upper (positive) or lower (negative) direction| |`total_vals`|numeric|the total number of values| |`sd_threshold`|numeric|the number of standard deviations a value should fall in either direction of the mean to be considered an outlier| |`time_start`|date|the start of the time period being examined| |`time_increment`|character|the length of each time period| |`n_outlier`|numeric|the number of outlying values| |`prop_outlier`|numeric|the proportion of outlying values| |`output_function`|character|a string indicating the type of visualization that should be generated by qvd_output| {.dqcheck-table} |
| local.description.viz | This check outputs a line graph visualizing the proportion of values that are considered outliers (based on the number of standard devations they fall from the mean) across the time span. The outliers are stratified by upper and lower outlier types so the user can differentiate between outliers above and below the mean at each time point. |
| local.dqcheck.requirement | cohort |
| local.dqcheck.requirement | qvd_value_file |
| local.dqcheck.requirement | omop_or_pcornet |
| local.dqcheck.requirement | multi_or_single_site |
| local.dqcheck.requirement | anomaly_or_exploratory |
| local.dqcheck.requirement | age_groups |
| local.dqcheck.requirement | time |
| local.dqcheck.requirement | sd_threshold |
| local.subject.flat | Plausibility |
| local.subject.flat | Line Graph |
| local.subject.flat | Event-Level Analysis |
| local.subject.flat | Clinical Data Distributions |
| local.subject.flat | Clinical Consistency |
| local.subject.flat | Selection Error or Bias Detection |
| local.subject.flat | Information Density |
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