## ----library, echo=TRUE, message=FALSE, warning=FALSE, results="hide"--------- library(teal.modules.general) # used to create the app library(dplyr) # used to modify data sets ## ----data, echo=TRUE, message=FALSE, warning=FALSE, results="hide"------------ data <- teal_data() data <- within(data, { ADSL <- teal.data::rADSL %>% mutate(TRTDUR = round(as.numeric(TRTEDTM - TRTSDTM), 1)) ADRS <- teal.data::rADRS ADTTE <- teal.data::rADTTE ADLB <- teal.data::rADLB %>% mutate(CHGC = as.factor(case_when( CHG < 1 ~ "N", CHG > 1 ~ "P", TRUE ~ "-" ))) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ## ----app, echo=TRUE, message=FALSE, warning=FALSE, results="hide"------------- # configuration for the single wide dataset mod1 <- tm_a_regression( label = "Single wide dataset", response = data_extract_spec( dataname = "ADSL", select = select_spec( label = "Select variable:", choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2")), selected = "BMRKR1", multiple = FALSE, fixed = FALSE ) ), regressor = data_extract_spec( dataname = "ADSL", select = select_spec( label = "Select variables:", choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE")), selected = "AGE", multiple = TRUE, fixed = FALSE ) ) ) # configuration for the two wide datasets mod2 <- tm_a_regression( label = "Two wide datasets", default_plot_type = 2, response = data_extract_spec( dataname = "ADSL", select = select_spec( label = "Select variable:", choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2")), selected = "BMRKR1", multiple = FALSE, fixed = FALSE ) ), regressor = data_extract_spec( dataname = "ADSL", select = select_spec( label = "Select variables:", choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE")), selected = c("AGE", "RACE"), multiple = TRUE, fixed = FALSE ) ) ) # configuration for the same long datasets (same subset) mod3 <- tm_a_regression( label = "Same long datasets (same subset)", default_plot_type = 2, response = data_extract_spec( dataname = "ADTTE", select = select_spec( label = "Select variable:", choices = variable_choices(data[["ADTTE"]], c("AVAL", "CNSR")), selected = "AVAL", multiple = FALSE, fixed = FALSE ), filter = filter_spec( label = "Select parameter:", vars = "PARAMCD", choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"), selected = "PFS", multiple = FALSE ) ), regressor = data_extract_spec( dataname = "ADTTE", select = select_spec( label = "Select variable:", choices = variable_choices(data[["ADTTE"]], c("AGE", "CNSR", "SEX")), selected = c("AGE", "CNSR", "SEX"), multiple = TRUE ), filter = filter_spec( label = "Select parameter:", vars = "PARAMCD", choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"), selected = "PFS", multiple = FALSE ) ) ) # configuration for the wide and long datasets mod4 <- tm_a_regression( label = "Wide and long datasets", response = data_extract_spec( dataname = "ADLB", filter = list( filter_spec( vars = "PARAMCD", choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"), selected = levels(data[["ADLB"]]$PARAMCD)[2], multiple = TRUE, label = "Select measurement:" ), filter_spec( vars = "AVISIT", choices = levels(data[["ADLB"]]$AVISIT), selected = levels(data[["ADLB"]]$AVISIT)[2], multiple = TRUE, label = "Select visit:" ) ), select = select_spec( label = "Select variable:", choices = "AVAL", selected = "AVAL", multiple = FALSE, fixed = TRUE ) ), regressor = data_extract_spec( dataname = "ADSL", select = select_spec( label = "Select variables:", choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2", "AGE")), selected = "AGE", multiple = TRUE, fixed = FALSE ) ) ) # configuration for the same long datasets (different subsets) mod5 <- tm_a_regression( label = "Same long datasets (different subsets)", default_plot_type = 2, response = data_extract_spec( dataname = "ADLB", filter = list( filter_spec( vars = "PARAMCD", choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"), selected = levels(data[["ADLB"]]$PARAMCD)[1], multiple = TRUE, label = "Select lab:" ), filter_spec( vars = "AVISIT", choices = levels(data[["ADLB"]]$AVISIT), selected = levels(data[["ADLB"]]$AVISIT)[1], multiple = TRUE, label = "Select visit:" ) ), select = select_spec( choices = "AVAL", selected = "AVAL", multiple = FALSE, fixed = TRUE ) ), regressor = data_extract_spec( dataname = "ADLB", filter = list( filter_spec( vars = "PARAMCD", choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"), selected = levels(data[["ADLB"]]$PARAMCD)[1], multiple = FALSE, label = "Select labs:" ), filter_spec( vars = "AVISIT", choices = levels(data[["ADLB"]]$AVISIT), selected = levels(data[["ADLB"]]$AVISIT)[1], multiple = FALSE, label = "Select visit:" ) ), select = select_spec( choices = variable_choices(data[["ADLB"]], c("AVAL", "AGE", "BMRKR1", "BMRKR2", "SEX", "ARM")), selected = c("AVAL", "BMRKR1"), multiple = TRUE ) ) ) # initialize the app app <- init( data = data, modules = modules( modules( label = "Regression plots", mod1, mod2, mod3, mod4, mod5 ) ) ) ## ----shinyapp, eval=FALSE----------------------------------------------------- # shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024)) ## ----shinylive_url, echo = FALSE, results = 'asis', eval = requireNamespace("roxy.shinylive", quietly = TRUE)---- code <- paste0(c( knitr::knit_code$get("library"), knitr::knit_code$get("data"), knitr::knit_code$get("app"), knitr::knit_code$get("shinyapp") ), collapse = "\n") url <- roxy.shinylive::create_shinylive_url(code) cat(sprintf("[Open in Shinylive](%s)\n\n", url)) ## ----shinylive_iframe, echo = FALSE, out.width = '150%', out.extra = 'style = "position: relative; z-index:1"', eval = requireNamespace("roxy.shinylive", quietly = TRUE) && knitr::is_html_output() && identical(Sys.getenv("IN_PKGDOWN"), "true")---- # knitr::include_url(url, height = "800px")