R: Modified Detecting Deviating Cells Algorithm in Pharmacovigilance

# Modified Detecting Deviating Cells Algorithm in Pharmacovigilance

## Documentation for package ‘MDDC’ version 1.1.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

MDDC-package | Modified Detecting Deviating Cells Algorithm in Pharmacovigilance
betablocker500 | FDA dataset for beta blockers with 500 adverse events
check_and_fix_contin_table | Verifying and correcting the input I by J contingency table
find_optimal_coef | Find Adaptive Boxplot Coefficient 'coef' via Grid Search
generate_contin_table_with_clustered_AE | Generate simulated contingency tables with the option of incorporating adverse event correlation within clusters.
generate_contin_table_with_clustered_AE_with_tol | Generate simulated contingency tables with the option of incorporating adverse event correlation within clusters and tolerance for total report count.
get_expected_counts | Compute the Expected Count Matrix from a Contingency Table
get_std_pearson_res | Computing the standardized Pearson residuals for a given I \times J contingency table
MDDC | Modified Detecting Deviating Cells Algorithm in Pharmacovigilance
mddc_boxplot | Modified Detecting Deviating Cells (MDDC) algorithm for adverse event signal identification with boxplot method for cutoff selection.
mddc_mc | Modified Detecting Deviating Cells (MDDC) algorithm for adverse event signal identification with Monte Carlo (MC) method for cutoff selection.
plot_heatmap | Plot Heatmap
report_drug_AE_pairs | Report the potential adverse events for drugs from contingency table
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