populated_effects_table.RdGenerate populated effects table with calculated CIs
populated_effects_table(data)Effects tble with calculated CIs
effects_table <- populated_effects_table(effects_table)
#> [2024-08-28 08:20:51] >
#> absolute risk CI for binary outcomes is calculated and saved
#> [2024-08-28 08:20:51] >
#> CI for relative risk for binary outcomes is calculated
#> [2024-08-28 08:20:51] >
#> CI for odds ratio for binary outcomes is calculated and saved
#> [2024-08-28 08:20:51] >
#> CI for treatment difference in continuous outcomes is calculated
#> [2024-08-28 08:20:51] >
#> CI for treatment difference in exposure-adjusted rates
#> is calculated and saved in a dataframe
#> [2024-08-28 08:20:51] >
#> CI for treatment difference in exposure-adjusted rates
#> is calculated and saved in a dataframe
#> [2024-08-28 08:20:51] > Generate populated effects table with calculated CIs
head(effects_table)
#> Factor Grouped_Outcome Outcome Statistics
#> 1 Benefit Clinical Assessment Primary Efficacy % Achieving Remission
#> 2 Benefit Clinical Assessment Secondary Efficacy Mean Change from Baseline
#> 3 Benefit Quality of Life HR Quality of Life Mean Change from Baseline
#> 4 Risk Adverse Event Reoccurring AE Event Rate
#> 5 Risk Adverse Event Rare SAE Incidence Rate
#> 6 Risk Toxicity Liver Incidence Rate
#> Type Rate_Type Outcome_Status Filter Category Trt1 nSub1 N1 Prop1
#> 1 Binary <NA> Identified None All Drug A 300 1000 0.460
#> 2 Continuous <NA> Identified None All Drug A NA 1000 NA
#> 3 Continuous <NA> Identified None All Drug A NA 1000 NA
#> 4 Binary EventRate Identified None All Drug A 300 1000 0.190
#> 5 Binary IncRate Identified None All Drug A 15 1000 0.015
#> 6 Binary IncRate Potential None All Drug A 4 1000 0.004
#> Dur1 100PYAR1 IncRate1 nEvent1 100PEY1 EventRate1 Mean1 Se1 Sd1 Drug_Status
#> 1 365 NA NA NA NA NA NA NA NA Approved
#> 2 365 NA NA NA NA NA 65 NA 63 Approved
#> 3 NA NA NA NA NA NA 60 NA 60 Approved
#> 4 365 NA NA 750 1000 0.75 NA NA NA Approved
#> 5 365 1000 0.300 NA NA NA NA NA NA Approved
#> 6 365 1000 0.015 NA NA NA NA NA NA Approved
#> Trt2 nSub2 N2 Prop2 Dur2 100PYAR2 IncRate2 nEvent2 100PEY2 EventRate2
#> 1 Placebo 50 1000 0.050 365 NA NA NA NA NA
#> 2 Placebo NA 1000 NA NA NA NA NA NA NA
#> 3 Placebo NA 1000 NA NA NA NA NA NA NA
#> 4 Placebo 30 1000 0.030 365 NA NA 30 1000 0.03
#> 5 Placebo 1 1000 0.002 365 1000 0.001 NA NA NA
#> 6 Placebo 1 1000 0.001 365 1000 0.001 NA NA NA
#> Mean2 Se2 Sd2 Diff_LowerCI Diff_UpperCI Diff_IncRate_LowerCI
#> 1 NA NA NA 0.376285201 0.443714799 NA
#> 2 20 NA 16 40.968890317 49.031109683 NA
#> 3 9 NA 8 47.246045616 54.753954384 NA
#> 4 NA NA NA 0.133486099 0.186513901 NA
#> 5 NA NA NA 0.004973475 0.021026525 0.264995896
#> 6 NA NA NA -0.001375156 0.007375156 0.006160144
#> Diff_IncRate_UpperCI Diff_EventRate_LowerCI Diff_EventRate_UpperCI
#> 1 NA NA NA
#> 2 NA NA NA
#> 3 NA NA NA
#> 4 NA 0.6652612 0.7747388
#> 5 0.33300410 NA NA
#> 6 0.02183986 NA NA
#> RelRisk_LowerCI RelRisk_UpperCI OddsRatio_LowerCI OddsRatio_UpperCI
#> 1 6.9644608 12.153130 11.8664287 22.07574
#> 2 NA NA NA NA
#> 3 NA NA NA NA
#> 4 4.3530706 9.214441 5.1033367 11.27156
#> 5 1.7196172 32.710769 1.7332246 33.31626
#> 6 0.4478673 35.724866 0.4476421 35.95848
#> MCDA_Weight Population Data_Source Quality Notes
#> 1 NA NA NA NA NA
#> 2 NA NA NA NA NA
#> 3 NA NA NA NA NA
#> 4 NA NA NA NA NA
#> 5 NA NA NA NA NA
#> 6 NA NA NA NA NA