hiersim - Stata program to simulate hierarchical clinical registry data and apply benchmarking and outlier classification methods

A user-written Stata program to simulate hierarchical (3 level) clinical registry data with known outlying sites using specified parameters, run regression models, apply outlier classification methods, flag outliers and compare to true, storing and saving performance measures and dataset features. T...

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Main Author: Jessy Hansen
Format: Software
Language:unknown
Published: 2023
Subjects:
Online Access:https://doi.org/10.26180/24480889.v1
https://figshare.com/articles/software/hiersim_-_Stata_program_to_simulate_hierarchical_clinical_registry_data_and_apply_benchmarking_and_outlier_classification_methods/24480889
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spelling ftmonashunivfig:oai:figshare.com:article/24480889 2023-12-03T10:23:38+01:00 hiersim - Stata program to simulate hierarchical clinical registry data and apply benchmarking and outlier classification methods Jessy Hansen 2023-11-03T04:31:29Z https://doi.org/10.26180/24480889.v1 https://figshare.com/articles/software/hiersim_-_Stata_program_to_simulate_hierarchical_clinical_registry_data_and_apply_benchmarking_and_outlier_classification_methods/24480889 unknown doi:10.26180/24480889.v1 https://figshare.com/articles/software/hiersim_-_Stata_program_to_simulate_hierarchical_clinical_registry_data_and_apply_benchmarking_and_outlier_classification_methods/24480889 CC BY 4.0 Biostatistics Clinical registry Simulated data Stata program Software 2023 ftmonashunivfig https://doi.org/10.26180/24480889.v1 2023-11-09T00:09:54Z A user-written Stata program to simulate hierarchical (3 level) clinical registry data with known outlying sites using specified parameters, run regression models, apply outlier classification methods, flag outliers and compare to true, storing and saving performance measures and dataset features. The program allows for the specification of ten data parameters: outcome prevalence (prev), outlier definition (using a risk quotient, rq), proportion of outliers (op), site dispersion (using site SD, ssdint), risk-adjustment fit (using risk factor SD, rfsd), clinician variance (using clinician:site SD ratio, csdr), number of sites (siten), clinicians (clinn) and patients (totn), and case volume minimum (cvmin). Parameters can be varied iteratively one at a time or in a factorial framework. Estimates for benchmarking can be obtained from four different methods: unadjusted rates (raw), and rates obtained from ordinary (ord), conditional fixed effects (fe) or random-intercept effects (re) logistic regression. Outlier classification using confidence interval or control limits techniques can be applied. A selection of four confidence interval and three control limit methods are available: Byar approximation (cib), exact Poisson (cid), Rothman & Greenland (cir), Vandenbrouke (civ), exact binomial (cle), Wald (clw), false discovery rate (fdr), with the confidence/control level specified as desired. The number of simulations (nsim), risk factor odds ratio (rfor) and starting seed (seed) can be optionally specified. Stata syntax: Required: prev(numlist) rq(numlist) op(numlist) ssdint(numlist) rfsd(numlist) csdr(numlist) siten(numlist) clinn(numlist) totn(numlist) cvmin(numlist) - list of parameter values, at least one value required for all parameters, first value taken as the default for that parameter saving(string) - specify location to save results from the simulation Optional: ff(string) - specify parameter to be varied in a fully factorial design (default base) model(string) - specify list of estimate methods, ... Software Greenland Monash University: Figshare Greenland
institution Open Polar
collection Monash University: Figshare
op_collection_id ftmonashunivfig
language unknown
topic Biostatistics
Clinical registry
Simulated data
Stata program
spellingShingle Biostatistics
Clinical registry
Simulated data
Stata program
Jessy Hansen
hiersim - Stata program to simulate hierarchical clinical registry data and apply benchmarking and outlier classification methods
topic_facet Biostatistics
Clinical registry
Simulated data
Stata program
description A user-written Stata program to simulate hierarchical (3 level) clinical registry data with known outlying sites using specified parameters, run regression models, apply outlier classification methods, flag outliers and compare to true, storing and saving performance measures and dataset features. The program allows for the specification of ten data parameters: outcome prevalence (prev), outlier definition (using a risk quotient, rq), proportion of outliers (op), site dispersion (using site SD, ssdint), risk-adjustment fit (using risk factor SD, rfsd), clinician variance (using clinician:site SD ratio, csdr), number of sites (siten), clinicians (clinn) and patients (totn), and case volume minimum (cvmin). Parameters can be varied iteratively one at a time or in a factorial framework. Estimates for benchmarking can be obtained from four different methods: unadjusted rates (raw), and rates obtained from ordinary (ord), conditional fixed effects (fe) or random-intercept effects (re) logistic regression. Outlier classification using confidence interval or control limits techniques can be applied. A selection of four confidence interval and three control limit methods are available: Byar approximation (cib), exact Poisson (cid), Rothman & Greenland (cir), Vandenbrouke (civ), exact binomial (cle), Wald (clw), false discovery rate (fdr), with the confidence/control level specified as desired. The number of simulations (nsim), risk factor odds ratio (rfor) and starting seed (seed) can be optionally specified. Stata syntax: Required: prev(numlist) rq(numlist) op(numlist) ssdint(numlist) rfsd(numlist) csdr(numlist) siten(numlist) clinn(numlist) totn(numlist) cvmin(numlist) - list of parameter values, at least one value required for all parameters, first value taken as the default for that parameter saving(string) - specify location to save results from the simulation Optional: ff(string) - specify parameter to be varied in a fully factorial design (default base) model(string) - specify list of estimate methods, ...
format Software
author Jessy Hansen
author_facet Jessy Hansen
author_sort Jessy Hansen
title hiersim - Stata program to simulate hierarchical clinical registry data and apply benchmarking and outlier classification methods
title_short hiersim - Stata program to simulate hierarchical clinical registry data and apply benchmarking and outlier classification methods
title_full hiersim - Stata program to simulate hierarchical clinical registry data and apply benchmarking and outlier classification methods
title_fullStr hiersim - Stata program to simulate hierarchical clinical registry data and apply benchmarking and outlier classification methods
title_full_unstemmed hiersim - Stata program to simulate hierarchical clinical registry data and apply benchmarking and outlier classification methods
title_sort hiersim - stata program to simulate hierarchical clinical registry data and apply benchmarking and outlier classification methods
publishDate 2023
url https://doi.org/10.26180/24480889.v1
https://figshare.com/articles/software/hiersim_-_Stata_program_to_simulate_hierarchical_clinical_registry_data_and_apply_benchmarking_and_outlier_classification_methods/24480889
geographic Greenland
geographic_facet Greenland
genre Greenland
genre_facet Greenland
op_relation doi:10.26180/24480889.v1
https://figshare.com/articles/software/hiersim_-_Stata_program_to_simulate_hierarchical_clinical_registry_data_and_apply_benchmarking_and_outlier_classification_methods/24480889
op_rights CC BY 4.0
op_doi https://doi.org/10.26180/24480889.v1
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