Data Quality Modules

 

Permanent URI for this collectionhttps://pedsnet.org/metadata/handle/20.500.14642/2

In this collection, explore dozens of study-specific and network data quality analysis modules. These modules facilitate the objective exploration and presentation of study and network data, thereby ensuring that research analyses are conducted under the assumption of producing valid results. Navigate the Subcollections and Domains to explore categories of data quality analysis and available modules, or browse by Subject Category to use data quality classifications for identifying checks relevant to your research stage. Learn more about the PEDSnet Data Quality program here.

Browse the hierarchy of terms below for definitions of our data quality classifications.

Data Quality Category

Overarching characterization of a module's purpose.

View Data Quality Categories

Dataset Evaluation Strategy

Characterizations of potential variables of interest, such as time, anomalies, data sources, or output.

View Dataset Evaluation Strategies

Analysis Level
Temporal Evaluation
Data Source Comparison
  • Multi-Site Analysis

    More than one source of data (i.e., contributing healthcare institution) is analyzed by the check, allowing for the direct comparison of data from each source.

  • Single Site Analysis

    A single source of data (i.e., contributing healthcare institution) is analyzed by the check.

Data Anomaly Method
Exploratory Analysis
Data Visualization
  • Bar Graph

    Output of a diagram in which the value of variables are represented by the height of the bar.

  • Control Chart

    Output of a time-series graph which displays how a process changes over time. Includes a center line, an upper control limit and a lower control limit.


Error Detection Approach

Classifications of data quality probes, clinical and general.

View Error Detection Approach Classes

Data Quality Probe
Clinical Probe

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Collections in this Collection

Now showing 1 - 6 of 6
  • Cohort Fitness  
    Modules to evaluate the face validity of a cohort for a given analysis.
  • Cohort Identification  
    Modules to evaluate the formation and quality of a study cohort.
  • Concept Set Testing  
    Modules to evaluate concept-set distributions and plausibility in a clinical dataset.
  • Data Conformance  
    Modules to assess the conformance of data to the data model.
  • Dataset Fitness  
    Modules to assess dataset quality and consistency, with a focus on the overall fitness of a dataset rather than specific variables or concepts.
  • Variable Testing  
    Modules to understand variable distributions and representations within a clinical dataset.

Domains in this Collection

Now showing 1 - 1 of 1