Expected Variables Present: Multi-Site, Anomaly Detection, Cross-Sectional Analysis


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dc.contributorPatient-Centered Outcomes Research Institute
dc.contributor.authorPEDSnet Data Coordinating Center
dc.contributor.otherPEDSnet Data Coordinating Center
dc.date.accessioned2024-09-09T17:20:49Z
dc.date.created2024-06-05
dc.description.abstractThis check provides raw data and visualizations to aid a user in evaluating whether expected concepts are present in a dataset of interest. It summarizes the proportion of patients with co-occurring variables. This check promotes the identification of anomalous data to compare among sites.
dc.identifier.urihttps://hdl.handle.net/20.500.14642/779
dc.identifier.urihttps://doi.org/10.24373/pdsp-461
dc.publisherPEDSnet
dc.relation.urihttps://github.com/ssdqa/expectedvariablespresent
dc.rightsa CC-BY Attribution 4.0 License.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0
dc.subjectMulti-Site Analysis
dc.subjectData Anomaly Method
dc.subjectCross-Sectional Analysis
dc.subjectPerson-Level Analysis
dc.titleExpected Variables Present: Multi-Site, Anomaly Detection, Cross-Sectional Analysis
dspace.entity.typeDQCheck
local.code.package# install.packages("devtools") devtools::install_github('ssdqa/https://github.com/ssdqa/conceptsetdistribution')
local.description.rawThe raw data output of this check produces twenty_one columns of data: <br> | Column | Data Type | Definition | |-------------------|-----------|-----------------------------------------------------------------------------------------------------------------------------| |`site` | character | the name of the site being targeted | |`total_pt_ct` | numeric | the total number of patients from the cohort in the domain table | |`total_row_ct` | numeric | the total number of rows associated with patients from the cohort in the domain table | |`variable_pt_ct` | numeric | the number of patients with evidence of the variable | |`variable_row_ct` | numeric | the number of rows with evidence of the variable | |`prop_pt_variable` | numeric | the proportion of patients with evidence of the variable | |`prop_row_variable` | numeric | the proportion of rows with evidence of the variable | |`variable` | character | the name of the variable | |`mean_val` | numeric | the mean proportion of patients or rows (based on user selection) for each group across sites | |`median_val` | numeric | the median proportion of patients or rows (based on user selection) for each group across sites | |`sd_val` | numeric | the standard deviation of the proportion of patients or rows (based on user selection) for each group across sites | |`mad_val` | numeric | the median absolute deviation of the proportion of patients or rows (based on user selection) for each group across sites | |`cov_val` | numeric | the coefficient of variance of the proportion of patients or rows (based on user selection) for each group across sites | |`max_val` | numeric | the maximum proportion of patients or rows (based on user selection) for each group across sites | |`min_val` | numeric | the minimum prorportion of patients or rows (based on user selection) for each group across sites | |`range_val` | numeric | the range of the proportion of patients or rows (based on user selection) for each group across sites | |`total_ct` | numeric | the total number of group members | |`analysis_eligible` | character | a string indicating whether the group is eligible for anomaly detection analysis | |`lower_tail` | numeric | the lower bound used to identify low anomalies | |`upper_tail` | numeric | the upper bound used to identify high anomalies | |`anomaly_yn` | character | a string indicating whether the value is anomalous or not | {.dqcheck-table}
local.description.vizThis check outputs a dot plot representing anomalous proportions of patients (or rows) with a given variable per site. This graph summarizes the mean absolute deviation (MAD) value for the `concept_id` by the dot size, how often that `concept_id` is used proportionally by the dot color, and whether that `concept_id` is anomalous by replacing the dot with a star. A tooltip provides metadat for the mapped concet and the site and precise values for proportion, mean proportion, median proportion, standard deviation and MAD upon hover.
local.dqcheck.categoryCompleteness
local.dqcheck.clinicalprobeConfirmatory Clinical Data
local.dqcheck.clinicalprobeClinical Follow-Up
local.dqcheck.clinicalprobeClinical Complexity
local.dqcheck.measurementHotspots Outlier Detection
local.dqcheck.probeData Representation Errors
local.dqcheck.probeMisclassification Detection
local.dqcheck.probeExternal Benchmarking
local.dqcheck.probeMissing Required Data
local.dqcheck.requirementcohort
local.dqcheck.requirementomop_or_pcornet
local.dqcheck.requirementevp_variable_file
local.dqcheck.requirementmulti_or_single_site
local.dqcheck.requirementanomaly_or_exploratory
local.dqcheck.requirementoutput_level
local.dqcheck.requirementage_groups
local.dqcheck.requirementp_value
local.dqcheck.requirementtime
local.dqcheck.requirementtime_span
local.dqcheck.requirementtime_period
local.dqcheck.typeVariable Testing
local.dqcheck.vizDot and Star Plot
relation.isCodeOfDQCheck929c8dfc-2c8b-4e62-8e1d-0fa06c542832
relation.isCodeOfDQCheck.latestForDiscovery929c8dfc-2c8b-4e62-8e1d-0fa06c542832
relation.isDQResultOfDQCheckcb11c990-01dd-4191-b116-979d6016a514
relation.isDQResultOfDQCheck.latestForDiscoverycb11c990-01dd-4191-b116-979d6016a514

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Expected Variables Present