For the EGT03 template, data imputation should be avoided, and missing data explicit and accounted for, so the contingency table sum adds up to the group N. For illustration purposes, missing data are added to the example dataset.
Planned Arm Code Minimum Post-Baseline Assessment
Baseline Reference Range Indicator LOW NORMAL HIGH Missing
————————————————————————————————————————————————————————————————————————————————
ARM A (N=134)
LOW 1 (0.7%) 5 (3.7%) 0 0
NORMAL 36 (26.9%) 83 (61.9%) 0 1 (0.7%)
HIGH 2 (1.5%) 4 (3%) 0 0
Missing 1 (0.7%) 0 0 1 (0.7%)
ARM B (N=134)
LOW 1 (0.7%) 9 (6.7%) 0 0
NORMAL 40 (29.9%) 75 (56%) 0 2 (1.5%)
HIGH 1 (0.7%) 4 (3%) 0 0
Missing 1 (0.7%) 1 (0.7%) 0 0
ARM C (N=132)
LOW 4 (3%) 11 (8.3%) 0 0
NORMAL 31 (23.5%) 75 (56.8%) 0 0
HIGH 1 (0.8%) 8 (6.1%) 0 1 (0.8%)
Missing 1 (0.8%) 0 0 0
Experimental use!
WebR is a tool allowing you to run R code in the web browser. Modify the code below and click run to see the results. Alternatively, copy the code and click here to open WebR in a new tab.
For the EGT03 template, data imputation should be avoided, and missing data explicit and accounted for, so the contingency table sum adds up to the group N. For illustration purpose, missing data are added to the example dataset.
Planned Arm Code Maximum Post-Baseline Assessment
Baseline Reference Range Indicator LOW NORMAL HIGH Missing
————————————————————————————————————————————————————————————————————————————————
ARM A (N=134)
LOW 0 2 (1.5%) 4 (3%) 0
NORMAL 0 88 (65.7%) 31 (23.1%) 1 (0.7%)
HIGH 0 5 (3.7%) 1 (0.7%) 0
Missing 0 0 1 (0.7%) 1 (0.7%)
ARM B (N=134)
LOW 0 8 (6%) 2 (1.5%) 0
NORMAL 0 76 (56.7%) 39 (29.1%) 2 (1.5%)
HIGH 0 3 (2.2%) 2 (1.5%) 0
Missing 0 1 (0.7%) 1 (0.7%) 0
ARM C (N=132)
LOW 0 12 (9.1%) 3 (2.3%) 0
NORMAL 0 79 (59.8%) 27 (20.5%) 0
HIGH 0 5 (3.8%) 4 (3%) 1 (0.8%)
Missing 0 0 1 (0.8%) 0
Experimental use!
WebR is a tool allowing you to run R code in the web browser. Modify the code below and click run to see the results. Alternatively, copy the code and click here to open WebR in a new tab.
Code
library(tern)library(dplyr)adeg <- random.cdisc.data::cadeg# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels.adeg <-df_explicit_na(adeg)adeg_labels <-var_labels(adeg)adeg_f_pbmin <-subset( adeg, PARAMCD =="HR"&# Heart Rate SAFFL =="Y"&# "Safety Population Flag" ONTRTFL =="Y"&# "On Treatment Record Flag" AVISIT =="POST-BASELINE MINIMUM"# "Analysis Visit")adeg_f_pbmax <-subset( adeg, PARAMCD =="HR"&# Heart Rate SAFFL =="Y"&# "Safety Population Flag" ONTRTFL =="Y"&# "On Treatment Record Flag" AVISIT =="POST-BASELINE MAXIMUM"# "Analysis Visit")var_labels(adeg_f_pbmin) <- adeg_labelsvar_labels(adeg_f_pbmax) <- adeg_labels
library(teal.modules.clinical)## Data reproducible codedata <-teal_data()data <-within(data, { ADSL <- random.cdisc.data::cadsl ADEG <- random.cdisc.data::cadeg})datanames <-c("ADSL", "ADEG")datanames(data) <- datanames
Warning: `datanames<-()` was deprecated in teal.data 0.6.1.
ℹ invalid to use `datanames()<-` or `names()<-` on an object of class
`teal_data`. See ?names.teal_data
shinylive allow you to modify to run shiny application entirely in the web browser. Modify the code below and click re-run the app to see the results. The performance is slighly worse and some of the features (e.g. downloading) might not work at all.
