Package: MDDC 1.0.0

MDDC: Modified Detecting Deviating Cells Algorithm in Pharmacovigilance

Methods for detecting signals related to (adverse event, medical product e.g. drugs, vaccines) pairs, a data generation function for simulating pharmacovigilance datasets, and various utility functions. For more details please see Liu A., Mukhopadhyay R., and Markatou M. <doi:10.48550/arXiv.2410.01168>.

Authors:Anran Liu [aut, cre], Raktim Mukhopadhyay [aut], Marianthi Markatou [aut]

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MDDC/json (API)

# Install 'MDDC' in R:
install.packages('MDDC', repos = c('https://niuniular.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/niuniular/mddc/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • betablocker500 - FDA dataset for beta blockers with 500 adverse events
  • sedative1000 - FDA dataset for sedatives with 1000 adverse events
  • statin101 - FDA statin dataset with 101 adverse events
  • statin49 - FDA statin dataset with 49 adverse events
  • statin49_AE_idx - Cluster index of the FDA statin dataset with 49 adverse events

On CRAN:

Conda:

pharmacovigilancecpp

4.54 score 1 stars 4 scripts 160 downloads 10 exports 34 dependencies

Last updated 5 months agofrom:925f9e24a2. Checks:12 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 05 2025
R-4.5-win-x86_64OKMar 05 2025
R-4.5-mac-x86_64OKMar 05 2025
R-4.5-mac-aarch64OKMar 05 2025
R-4.5-linux-x86_64OKMar 05 2025
R-4.4-win-x86_64OKMar 05 2025
R-4.4-mac-x86_64OKMar 05 2025
R-4.4-mac-aarch64OKMar 05 2025
R-4.4-linux-x86_64OKMar 05 2025
R-4.3-win-x86_64OKMar 05 2025
R-4.3-mac-x86_64OKMar 05 2025
R-4.3-mac-aarch64OKMar 05 2025

Exports:check_and_fix_contin_tablefind_optimal_coefgenerate_contin_table_with_clustered_AEgenerate_contin_table_with_clustered_AE_with_tolget_expected_countsget_std_pearson_resmddc_boxplotmddc_mcplot_heatmapreport_drug_AE_pairs

Dependencies:clicodetoolscolorspacedoParallelfansifarverforeachggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppEigenrlangscalestibbleutf8vctrsviridisLitewithr

Usage Examples for MDDC in R

Rendered fromIntroduction_to_MDDC.Rmdusingknitr::rmarkdownon Mar 05 2025.

Last update: 2024-10-06
Started: 2024-08-20

Readme and manuals

Help Manual

Help pageTopics
Modified Detecting Deviating Cells Algorithm in PharmacovigilanceMDDC-package MDDC
FDA dataset for beta blockers with 500 adverse eventsbetablocker500
Verifying and correcting the input I by J contingency tablecheck_and_fix_contin_table
Find Adaptive Boxplot Coefficient `coef` via Grid Searchfind_optimal_coef
Generate simulated contingency tables with the option of incorporating adverse event correlation within clusters.generate_contin_table_with_clustered_AE
Generate simulated contingency tables with the option of incorporating adverse event correlation within clusters and tolerance for total report count.generate_contin_table_with_clustered_AE_with_tol
Compute the Expected Count Matrix from a Contingency Tableget_expected_counts
Computing the standardized Pearson residuals for a given I \times J contingency tableget_std_pearson_res
Modified Detecting Deviating Cells (MDDC) algorithm for adverse event signal identification with boxplot method for cutoff selection.mddc_boxplot
Modified Detecting Deviating Cells (MDDC) algorithm for adverse event signal identification with Monte Carlo (MC) method for cutoff selection.mddc_mc
Plot Heatmapplot_heatmap
Report the potential adverse events for drugs from contingency tablereport_drug_AE_pairs
FDA dataset for sedatives with 1000 adverse eventssedative1000
FDA statin dataset with 101 adverse eventsstatin101
FDA statin dataset with 49 adverse eventsstatin49
Cluster index of the FDA statin dataset with 49 adverse eventsstatin49_AE_idx