## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup, include=FALSE-----------------------------------------------------
library(dplyr)
library(tidyr)
library(magrittr)
library(Tplyr)
library(knitr)

## ----data prep, echo=FALSE----------------------------------------------------

t <- tplyr_table(tplyr_adas, TRTP, where=EFFFL == "Y" & ITTFL == "Y" & PARAMCD == "ACTOT" & ANL01FL == "Y") %>% 
  set_pop_data(tplyr_adsl) %>% 
  set_pop_treat_var(TRT01P) %>% 
  set_pop_where(EFFFL == "Y" & ITTFL == "Y") %>% 
  set_distinct_by(USUBJID) %>% 
  set_desc_layer_formats(
    'n' = f_str('xx', n),
    'Mean (SD)' = f_str('xx.x (xx.xx)', mean, sd),
    'Median (Range)' = f_str('xx.x (xxx;xx)', median, min, max)
  ) %>% 
  add_layer(
    group_desc(AVAL, where= AVISITN ==  0, by = "Baseline")
  ) %>% 
  add_layer(
    group_desc(AVAL, where= AVISITN == 24, by = "Week 24")
  ) %>% 
  add_layer(
    group_desc(CHG,  where= AVISITN == 24, by = "Change from Baseline")
  )

sum_data <- t %>% 
  build(metadata=TRUE) %>% 
  apply_row_masks(row_breaks = TRUE) %>% 
  select(row_id, starts_with('row_label'), 
         var1_Placebo, `var1_Xanomeline Low Dose`, `var1_Xanomeline High Dose`)

# I don't need the full model code for this example so just mock it up. 
# But if you want to see it, it's available here:
# https://github.com/RConsortium/submissions-pilot1/blob/694a207aca7e419513ffe16f6f5873526da1bdcb/R/eff_models.R#L17
model_portion <- tibble::tribble(
  ~"row_id",  ~"row_label1",                       ~"var1_Xanomeline Low Dose", ~"var1_Xanomeline High Dose",
  "x4_1",    "p-value(Dose Response) [1][2]",      "",                          "0.245",
  "x4_2",    "",                                   "",                          "",
  "x4_3",    "p-value(Xan - Placebo) [1][3]",	    "0.569",    	               "0.233",
  "x4_4",    "   Diff of LS Means (SE)",           "-0.5 (0.82)",               "-1.0 (0.84)",
  "x4_5",    "   95% CI",                          "(-2.1;1.1)",                "(-2.7;0.7)",
  "x4_6",    "",                                   "",                          "",
  "x4_7",    "p-value(Xan High - Xan Low) [1][3]", "",                          "0.520",
  "x4_8",    "   Diff of LS Means (SE)",           "",                          "-0.5 (0.84)",
  "x4_9",    "   95% CI",                          "",                          "(-2.2;1.1)"
)

full_data <- bind_rows(sum_data, model_portion) %>% 
  mutate(
    across(where(is.character), ~ replace_na(., ""))
  )




## ----view data----------------------------------------------------------------
kable(full_data)

## ----tplyr_meta---------------------------------------------------------------
m <- tplyr_meta(
  names = quos(a, b, c),
  filters = quos(a==1, b==2, c==3)
)
m

## ----extending tplyr_meta-----------------------------------------------------
m <- m %>% 
  add_variables(quos(x)) %>% 
  add_filters(quos(x == 'a'))

m

## ----build efficacy metadata--------------------------------------------------
# Overall model subset of data
meta <- tplyr_meta(
  names = quos(TRTP, EFFFL, ITTFL, ANL01FL, SITEGR1, AVISIT, AVISITN, PARAMCD, AVAL, BASE, CHG),
  filters = quos(EFFFL == "Y", ITTFL == "Y", PARAMCD == "ACTOT", ANL01FL == "Y", AVISITN == 24)
)

# Xan High / Placebo contrast
meta_xhp <- meta %>% 
  add_filters(quos(TRTP %in% c("Xanomeline High Dose", "Placebo")))

# Xan Low / Placbo Contrast
meta_xlp <- meta %>% 
  add_filters(quos(TRTP %in% c("Xanomeline Low Dose", "Placebo")))

# Xan High / Xan Low Contrast
meta_xlh <- meta %>% 
  add_filters(quos(TRTP %in% c("Xanomeline High Dose", "Xanomeline Low Dose")))

eff_meta <- tibble::tribble(
  ~"row_id",  ~"row_label1",                       ~"var1_Xanomeline Low Dose", ~"var1_Xanomeline High Dose",
  "x4_1",    "p-value(Dose Response) [1][2]",      NULL,                        meta,
  "x4_3",    "p-value(Xan - Placebo) [1][3]",	     meta_xlp,    	              meta_xhp,
  "x4_4",    "   Diff of LS Means (SE)",           meta_xlp,                    meta_xhp,
  "x4_5",    "   95% CI",                          meta_xlp,                    meta_xhp,
  "x4_7",    "p-value(Xan High - Xan Low) [1][3]", NULL,                        meta_xlh,
  "x4_8",    "   Diff of LS Means (SE)",           NULL,                        meta_xlh,
  "x4_9",    "   95% CI",                          NULL,                        meta_xlh
)

## ----anti_join1---------------------------------------------------------------
meta %>% 
  add_anti_join(
    join_meta = tplyr_meta(
      names = quos(TRT01P, EFFFL, ITTFL, SITEGR1),
      filters = quos(EFFFL == "Y", ITTFL == "Y")
    ),
    on = quos(USUBJID)
  )

## ----extending metadata-------------------------------------------------------
t <- append_metadata(t, eff_meta)

## ----get_metadata-------------------------------------------------------------
get_metadata(t)

## ----query custom metadata----------------------------------------------------
get_meta_subset(t, 'x4_1', "var1_Xanomeline High Dose") %>% 
  head() %>% 
  kable()

## ----metadata without Tplyr---------------------------------------------------
get_meta_subset(eff_meta, 'x4_1', "var1_Xanomeline High Dose", target=tplyr_adas) %>% 
  head() %>% 
  kable()

## ---- out.width=850, out.extra='style="border: 1px solid #464646;" allowfullscreen="" allow="autoplay"', echo=FALSE----
knitr::include_app("https://michael-stackhouse.shinyapps.io/Tplyr-efficacy-shiny-demo", height = "900px")