修改变量的值

Question

附完整数据：

id = c (2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)
vm = c("12", "13", "14", "15", "16", "17", "18" "19", "20", "21", "22", "23", "24")
GE = c("0", "0", "0", "0", "0" "0", "1", "0", "1", "0", "1","0", "1")
status = c("noinfection", "noinfection", "noinfection", "noinfection", "noinfection", "noinfection", "infection", "noinfection", "infection", "noinfection", "infection", "noinfection", "infection")
fichier <- data.frame(id, vm, GE, status)

我们已经获得了 18 个月和 24 个月访视时的 GE 变量值。无法将它们从我们的数据集中删除。我如何更改这些值，以便它们考虑到以前的访问？

GE = 0，如果所有之前的访问都值 0。

GE = 1，如果之前至少有一次访问值 1。

Answer 1

根据您的上一个问题，这些解决方案将会起作用。

场景 1a：使用“完整”数据更新场景 1

这可以使您的原始数据保持不变，例如即使 vm == 18 在“完整”数据中具有 GE == 1，状态仍将为“无感染”。我创建了 GE1 列，以便您可以看到该过程。如果您不希望最终结果中出现 GE1 列，请将 GE1 的所有实例更改为 tmp1：

library(dplyr)
library(tidyr)

id <- c (2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)
vm <- c("12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24")
GE <- c("0", "0", "0", "0", "0", "0", "1", "0", "1", "0", "1","0", "1")
status <- c("noinfection", "noinfection", "noinfection", "noinfection", "noinfection", "noinfection", "infection", "noinfection", "infection", "noinfection", "infection", "noinfection", "infection")
fichier <- data.frame(id, vm, GE, status)

fichier <- fichier |>
  mutate(across(c(vm, GE), as.integer)) |>
  group_by(id) |> # assuming your data may have multiple id values
  mutate(tmp = if_else(vm <= 18, 1, 2)) |>
  group_by(id, tmp) |>
  mutate(GE1 = if_else(vm %in% c(18, 24), NA, GE),
         GE1 = case_when(is.na(GE1) & sum(GE1, na.rm = TRUE) == 0 ~ 0,
                          is.na(GE1) & sum(GE1, na.rm = TRUE) > 0 ~ 1,
                          .default = GE1),
         status = if_else(GE1 == 1, "infection", "noinfection")) |>
  ungroup() |>
  select(-starts_with("tmp"))

场景 2a：基于“完整”数据更新场景 1

id <- c (2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)
vm <- c("12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24")
GE <- c("0", "0", "0", "0", "0", "0", "1", "0", "1", "0", "1","0", "1")
status <- c("noinfection", "noinfection", "noinfection", "noinfection", "noinfection", "noinfection", "infection", "noinfection", "infection", "noinfection", "infection", "noinfection", "infection")
fichier <- data.frame(id, vm, GE, status)

fichier <- fichier |>
  mutate(across(c(vm, GE), as.integer)) |>
  group_by(id) |> # assuming your data may have multiple id values
  mutate(tmp = if_else(vm <= 18, 1, 2)) |>
  group_by(id, tmp) |>
  mutate(GE1 = if_else(vm %in% c(18, 24), NA, GE),
         tmp1 = +(n_distinct(GE1, na.rm = TRUE) == 1),
         GE1 = case_when(is.na(GE1) & tmp1 == 1 & first(GE1) == 0 ~ 0,
                         is.na(GE1) & tmp1 == 1 & first(GE1) == 1 ~ 1,
                         .default = GE1),
         status = case_when(GE1 == 0 ~ "noinfection",
                            GE1 == 1 ~ "infection",
                            .default = "mixed")) |>
  ungroup() |>
  select(-starts_with("tmp"))