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jkatam's questions

Martin Hope
jkatam
Asked: 2025-02-28 16:53:07 +0800 CST
  • 5

Aqui está o programa que estou usando para resumir os dados adsl pelos grupos TRT01PN e SITEID, no entanto, recebo o erro e é do filtro, então basicamente se mais de uma variável de grupo for usada e se tentarmos filtrar, não funcionará, não tenho certeza do motivo, aqui está o código que tentei com dados de amostra

filter(if_all(all_of(group), ~ !is.na(.)))


Error in `map2()`:
ℹ In index: 1.
Caused by error in `filter()`:
ℹ In argument: `if_all(all_of(valid_group), ~!is.na(.))`.
Caused by error in `if_all()`:
ℹ In argument: `all_of(valid_group)`.
Caused by error in `all_of()`:
! Can't subset elements that don't exist.
✖ Elements `TRT01PN` and `SITEID` don't exist.

use os dados do pacote tidyCDISC

dput(head(adsl))
structure(list(STUDYID = structure(c("CDISCPILOT01", "CDISCPILOT01", 
"CDISCPILOT01", "CDISCPILOT01", "CDISCPILOT01", "CDISCPILOT01"
), label = "Study Identifier"), USUBJID = structure(c("01-701-1015", 
"01-701-1023", "01-701-1028", "01-701-1033", "01-701-1034", "01-701-1047"
), label = "Unique Subject Identifier"), SUBJID = structure(c("1015", 
"1023", "1028", "1033", "1034", "1047"), label = "Subject Identifier for the Study"), 
    SITEID = structure(c("701", "701", "701", "701", "701", "701"
    ), label = "Study Site Identifier"), SITEGR1 = structure(c("701", 
    "701", "701", "701", "701", "701"), label = "Pooled Site Group 1"), 
    ARM = structure(c("Placebo", "Placebo", "Xanomeline High Dose", 
    "Xanomeline Low Dose", "Xanomeline High Dose", "Placebo"), label = "Description of Planned Arm"), 
    TRT01P = structure(c("Placebo", "Placebo", "Xanomeline High Dose", 
    "Xanomeline Low Dose", "Xanomeline High Dose", "Placebo"), label = "Planned Treatment for Period 01"), 
    TRT01PN = structure(c(0, 0, 81, 54, 81, 0), label = "Planned Treatment for Period 01 (N)"), 
    TRT01A = structure(c("Placebo", "Placebo", "Xanomeline High Dose", 
    "Xanomeline Low Dose", "Xanomeline High Dose", "Placebo"), label = "Actual Treatment for Period 01"), 
    TRT01AN = structure(c(0, 0, 81, 54, 81, 0), label = "Actual Treatment for Period 01 (N)"), 
    TRTSDT = structure(c(16072, 15557, 15905, 16147, 16252, 15748
    ), label = "Date of First Exposure to Treatment", format.sas = "DATE9", class = "Date"), 
    TRTEDT = structure(c(16253, 15584, 16084, 16160, 16434, 15773
    ), label = "Date of Last Exposure to Treatment", format.sas = "DATE9", class = "Date"), 
    TRTDURD = structure(c(182, 28, 180, 14, 183, 26), label = "Total Treatment Duration (Days)"), 
    AVGDD = structure(c(0, 0, 77.7, 54, 76.9, 0), label = "Avg Daily Dose (as planned)"), 
    CUMDOSE = structure(c(0, 0, 13986, 756, 14067, 0), label = "Cumulative Dose (as planned)"), 
    AGE = structure(c(63, 64, 71, 74, 77, 85), label = "Age"), 
    AGEGR1 = structure(c("<65", "<65", "65-80", "65-80", "65-80", 
    ">80"), label = "Pooled Age Group 1"), AGEGR1N = structure(c(1, 
    1, 2, 2, 2, 3), label = "Pooled Age Group 1 (N)"), AGEU = structure(c("YEARS", 
    "YEARS", "YEARS", "YEARS", "YEARS", "YEARS"), label = "Age Units"), 
    RACE = structure(c("WHITE", "WHITE", "WHITE", "WHITE", "WHITE", 
    "WHITE"), label = "Race"), RACEN = structure(c(1, 1, 1, 1, 
    1, 1), label = "Race (N)"), SEX = structure(c("F", "M", "M", 
    "M", "F", "F"), label = "Sex"), ETHNIC = structure(c("HISPANIC OR LATINO", 
    "HISPANIC OR LATINO", "NOT HISPANIC OR LATINO", "NOT HISPANIC OR LATINO", 
    "NOT HISPANIC OR LATINO", "NOT HISPANIC OR LATINO"), label = "Ethnicity"), 
    SAFFL = structure(c("Y", "Y", "Y", "Y", "Y", "Y"), label = "Safety Population Flag"), 
    ITTFL = structure(c("Y", "Y", "Y", "Y", "Y", "Y"), label = "Intent-To-Treat Population Flag"), 
    EFFFL = structure(c("Y", "Y", "Y", "Y", "Y", "Y"), label = "Efficacy Population Flag"), 
    COMP8FL = structure(c("Y", "N", "Y", "N", "Y", "N"), label = "Completers of Week 8 Population Flag"), 
    COMP16FL = structure(c("Y", "N", "Y", "N", "Y", "N"), label = "Completers of Week 16 Population Flag"), 
    COMP24FL = structure(c("Y", "N", "Y", "N", "Y", "N"), label = "Completers of Week 24 Population Flag"), 
    DISCONFL = structure(c(NA, "Y", NA, "Y", NA, "Y"), label = "Did the Subject Discontinue the Study?"), 
    DSRAEFL = structure(c(NA, "Y", NA, NA, NA, "Y"), label = "Discontinued due to AE?"), 
    DTHFL = structure(c(NA_character_, NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_), label = "Subject Died?"), 
    BMIBL = structure(c(25.1, 30.4, 31.4, 28.8, 26.1, 30.4), label = "Baseline BMI (kg/m^2)"), 
    BMIBLGR1 = structure(c("25-<30", ">=30", ">=30", "25-<30", 
    "25-<30", ">=30"), label = "Pooled Baseline BMI Group 1"), 
    HEIGHTBL = structure(c(147.3, 162.6, 177.8, 175.3, 154.9, 
    148.6), label = "Baseline Height (cm)"), WEIGHTBL = structure(c(54.4, 
    80.3, 99.3, 88.5, 62.6, 67.1), label = "Baseline Weight (kg)"), 
    EDUCLVL = structure(c(16, 14, 16, 12, 9, 8), label = "Years of Education"), 
    DISONSDT = structure(c(14729, 13218, 14594, 14458, 15246, 
    14451), label = "Date of Onset of Disease", format.sas = "DATE9", class = "Date"), 
    DURDIS = structure(c(43.9, 76.4, 42.8, 55.3, 32.9, 42), label = "Duration of Disease (Months)"), 
    DURDSGR1 = structure(c(">=12", ">=12", ">=12", ">=12", ">=12", 
    ">=12"), label = "Pooled Disease Duration Group 1"), VISIT1DT = structure(c(16065, 
    15543, 15897, 16139, 16245, 15727), label = "Date of Visit 1", format.sas = "DATE9", class = "Date"), 
    RFSTDTC = structure(c("2014-01-02", "2012-08-05", "2013-07-19", 
    "2014-03-18", "2014-07-01", "2013-02-12"), label = "Subject Reference Start Date/Time"), 
    RFENDTC = structure(c("2014-07-02", "2012-09-02", "2014-01-14", 
    "2014-04-14", "2014-12-30", "2013-03-29"), label = "Subject Reference End Date/Time"), 
    VISNUMEN = structure(c(12, 5, 12, 5, 12, 6), label = "End of Trt Visit (Vis 12 or Early Term.)"), 
    RFENDT = structure(c(16253, 15585, 16084, 16174, 16434, 15793
    ), label = "Date of Discontinuation/Completion", format.sas = "DATE9", class = "Date"), 
    DCDECOD = structure(c("COMPLETED", "ADVERSE EVENT", "COMPLETED", 
    "STUDY TERMINATED BY SPONSOR", "COMPLETED", "ADVERSE EVENT"
    ), label = "Standardized Disposition Term"), EOSSTT = structure(c("COMPLETED", 
    "DISCONTINUED", "COMPLETED", "DISCONTINUED", "COMPLETED", 
    "DISCONTINUED"), label = "End of Study Status"), DCSREAS = structure(c(NA, 
    "Adverse Event", NA, "Sponsor Decision", NA, "Adverse Event"
    ), label = "Reason for Discontinuation from Study"), MMSETOT = structure(c(23, 
    23, 23, 23, 21, 23), label = "MMSE Total"), FASFL = structure(c("Y", 
    "Y", "Y", "Y", "Y", "Y"), label = "Full Analysis Set Population Flag"), 
    RANDFL = structure(c("Y", "Y", "Y", "Y", "Y", "Y"), label = "Randomized Population Flag"), 
    EOTSTT = structure(c("COMPLETED", "DISCONTINUED", "COMPLETED", 
    "DISCONTINUED", "COMPLETED", "DISCONTINUED"), label = "End of Treatment Status"), 
    DCTREAS = structure(c(NA, "Adverse Event", NA, "Sponsor Decision", 
    NA, "Adverse Event"), label = "Reason for Discontinuation of Treatment"), 
    DTHDT = structure(c(NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_), label = "Date of Death", class = "Date")), row.names = c(NA, 
-6L), class = c("tbl_df", "tbl", "data.frame"))

é isso que se tenta

library(tidyverse)
library(tidyCDISC)

# data
adsl <- tidyCDISC::adsl |> select(SITEID, TRT01PN, AGE, TRTDURD, AVGDD)

# function to summarize the numeric column 

adsl_summ <- function(.data, group=NULL, vars=NULL){
  #browser()
  group_syms <- syms(group)
  vars <- syms(vars)

  adsl <- .data |> select(!!!group_syms, !!!vars)
  
  var_name <- adsl |> select(- all_of(as.character(group_syms))) |> names()
  
adsl_list <- map(var_name, \(x) adsl |> select(!!!group_syms, all_of(x)))

map2_dfr(adsl_list, var_name, \(x,y) {
  
  ynam <- sym(y)

adsl |> group_by(!!!group_syms) |>  filter(if_all(all_of(group), ~ !is.na(.))) |>
  summarise(mean=mean(!!ynam),
  sd=sd(!!ynam),
  median=median(!!ynam),
  min=min(!!ynam),
  max=max(!!ynam)
  ) |> ungroup() |> mutate(name=y)

})

}

adsl_summ(adsl, group=c('TRT01PN','SITEID'), vars=c('AGE', 'TRTDURD', 'AVGDD'))
Martin Hope
jkatam
Asked: 2024-04-21 00:50:05 +0800 CST
  • 5

considere os seguintes dados

Data ss;
infile datalines;
input ename $;
datalines;
Ram
Sita
Ram
Arjun
Sita
Ram
Arjun
;
run;

#output

Ram
Sita
Arjun

Conheço outras abordagens, como classificar os dados por ename e depois usar o primeiro., mas dessa forma precisamos classificar os dados e a saída começará com Arjun, Ram e Sita. No entanto, precisamos manter a ordem como mencionei na saída esperada.

proc sort data=ss;
by ename;
run;

data want;
set ss;
by ename;
if first.ename;
run;
sas
Martin Hope
jkatam
Asked: 2024-04-21 00:39:32 +0800 CST
  • 5

Estou usando o código abaixo para gerar a média e o padrão da coluna numérica do dataframe da classe. Espero que os nomes das novas colunas sejam Age_mean, Age_std em vez de Age.Age_mean, Age.Age_std. não sei por que a Idade. é adicionalmente adicionado aos nomes das colunas

Aqui estão os dados e o código que usei

class <- structure(list(Name = c("Alfred", "Alice", "Barbara", "Carol", 
"Henry", "James", "Jane", "Janet", "Jeffrey", "John", "Joyce", 
"Judy", "Louise", "Mary", "Philip", "Robert", "Ronald", "Thomas", 
"William"), Sex = c("M", "F", "F", "F", "M", "M", "F", "F", "M", 
"M", "F", "F", "F", "F", "M", "M", "M", "M", "M"), Age = c(14, 
13, 13, 14, 14, 12, 12, 15, 13, 12, 11, 14, 12, 15, 16, 12, 15, 
11, 15), Height = c(69, 56.5, 65.3, 62.8, 63.5, 57.3, 59.8, 62.5, 
62.5, 59, 51.3, 64.3, 56.3, 66.5, 72, 64.8, 67, 57.5, 66.5), 
    Weight = c(112.5, 84, 98, 102.5, 102.5, 83, 84.5, 112.5, 
    84, 99.5, 50.5, 90, 77, 112, 150, 128, 133, 85, 112)), class = c("tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -19L))


out1 <- list()

calc_mean <- function(data, vars, out) {
 
  vars <- syms(vars)
  print(vars)
  for (v in vars){
    print(v)
  out1[[v]] <- data %>% summarise('{{v}}_mean' := mean(!! v), '{{v}}_std' := sd(!! v))
  out2 <-  data.frame(out1)
  assign(out, out2, envir =.GlobalEnv)
  }

  return(out2)
}

calc_mean(data=class, vars=c('Age','Height'), out='want')

saída

  Age.Age_mean Age.Age_std Height.Height_mean Height.Height_std
1     13.31579    1.492672           62.33684          5.127075