Parameter Code ARM A ARM B ARM C
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BFIALL
Adjusted mean
n 134 134 132
Adjusted Mean 4.47 6.33 4.02
Difference in Adjusted Means 1.85 -0.46
95% CI (-0.14, 3.85) (-2.45, 1.54)
p-value 0.0679 0.6539
FATIGI
Adjusted mean
n 134 134 132
Adjusted Mean 5.42 4.83 4.56
Difference in Adjusted Means -0.59 -0.86
95% CI (-2.58, 1.41) (-2.87, 1.15)
p-value 0.5644 0.4026
FKSI-FWB
Adjusted mean
n 134 134 132
Adjusted Mean 4.29 3.51 3.06
Difference in Adjusted Means -0.79 -1.24
95% CI (-2.71, 1.14) (-3.17, 0.69)
p-value 0.4221 0.2088
FKSI-TSE
Adjusted mean
n 134 134 132
Adjusted Mean 4.70 3.84 4.45
Difference in Adjusted Means -0.86 -0.25
95% CI (-2.80, 1.09) (-2.20, 1.70)
p-value 0.3858 0.8007
FKSIALL
Adjusted mean
n 134 134 132
Adjusted Mean 5.03 5.82 6.44
Difference in Adjusted Means 0.79 1.42
95% CI (-1.17, 2.76) (-0.56, 3.39)
p-value 0.4288 0.1591
Experimental use!
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Code
library(tern)library(dplyr)adsl <- random.cdisc.data::cadsladqs <- random.cdisc.data::cadqs# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels.adsl <-df_explicit_na(adsl)adqs <-df_explicit_na(adqs)adqs_multi <-filter(adqs, AVISIT =="WEEK 1 DAY 8")
library(teal.modules.clinical)## Data reproducible codedata <-teal_data()data <-within(data, { ADSL <- random.cdisc.data::cadsl ADQS <- random.cdisc.data::cadqs# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels. ADSL <-df_explicit_na(ADSL) ADQS <-df_explicit_na(ADQS)})datanames <-c("ADSL", "ADQS")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
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