R new syntax for rCSI

Indicators/Reduced-coping-strategy-index/rCSI.R

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+# ------------------------------------------------------------
+# WFP Standardized Scripts
+# Reduced Coping Strategies Index (rCSI)
+# Last Updated: January 2026
+# ------------------------------------------------------------
+
+library(dplyr)
+
+# rCSI strategy variables (Survey Designer naming)
+rcsi_vars <- c(
+  "rCSILessQlty",
+  "rCSIBorrow",
+  "rCSIMealNb",
+  "rCSIMealSize",
+  "rCSIMealAdult"
+)
+
+# ------------------------------------------------------------
+# 1) Check individual strategies
+# ------------------------------------------------------------
+rcsi_stats_before <- df %>%
+  summarise(across(all_of(rcsi_vars),
+                   list(min  = ~min(as.numeric(.x), na.rm = TRUE),
+                        max  = ~max(as.numeric(.x), na.rm = TRUE),
+                        mean = ~mean(as.numeric(.x), na.rm = TRUE))))
+rcsi_stats_before
+
+# ------------------------------------------------------------
+# 2) Clean impossible values
+# ------------------------------------------------------------
+df <- df %>%
+  mutate(across(all_of(rcsi_vars), ~ as.numeric(.x))) %>%
+  mutate(across(all_of(rcsi_vars),
+                ~ ifelse(.x < 0 | .x >= 8, NA_real_, .x)))
+
+# ------------------------------------------------------------
+# 3) Compute rCSI
+# ------------------------------------------------------------
+df <- df %>%
+  mutate(
+    rCSI = (rCSILessQlty * 1) +
+      (rCSIBorrow   * 2) +
+      (rCSIMealNb   * 1) +
+      (rCSIMealSize * 1) +
+      (rCSIMealAdult* 3)
+  )
+
+# ------------------------------------------------------------
+# 4) Clean impossible rCSI values
+#    Expected range: 0–56
+# ------------------------------------------------------------
+df <- df %>%
+  mutate(
+    rCSI = ifelse(rCSI < 0 | rCSI >= 57, NA_real_, rCSI)
+  )
+
+# ------------------------------------------------------------
+# 5) Data quality flags
+# ------------------------------------------------------------
+df <- df %>%
+  mutate(
+    rCSI_flag_low  = ifelse(!is.na(rCSI) & rCSI <= 3,  1L, 0L),
+    rCSI_flag_high = ifelse(!is.na(rCSI) & rCSI >= 42, 1L, 0L)
+  )
+
+# Flag distributions
+table(df$rCSI_flag_low,  useNA = "ifany")
+table(df$rCSI_flag_high, useNA = "ifany")
+
+# ------------------------------------------------------------
+# 6) Distribution check of rCSI
+# ------------------------------------------------------------
+c(
+  mean = mean(df$rCSI, na.rm = TRUE),
+  sd   = sd(df$rCSI,   na.rm = TRUE),
+  min  = min(df$rCSI,  na.rm = TRUE),
+  max  = max(df$rCSI,  na.rm = TRUE)
+)
+
+# ------------------------------------------------------------
+# 7) Optional IPC classification (standard)
+# ------------------------------------------------------------
+
+df <- df %>%
+  mutate(
+    rCSI_IPC = case_when(
+      is.na(rCSI)        ~ NA_integer_,
+      rCSI <= 3          ~ 1L,
+      rCSI >= 4 & rCSI <= 18 ~ 2L,
+      rCSI >= 19         ~ 3L
+    ),
+    rCSI_IPC = factor(
+      rCSI_IPC,
+      levels = c(1,2,3),
+      labels = c("rCSI [0–3] - IPC Phase 1",
+                 "rCSI [4–18] - IPC Phase 2",
+                 "rCSI [≥19] - IPC Phase 3–5")
+    )
+  )
+
+table(df$rCSI_IPC, useNA = "ifany")
+
+# ------------------------------------------------------------
+# 8) Optional IPC classification – high values (potential Phase 4)
+# ------------------------------------------------------------
+df <- df %>%
+  mutate(
+    rCSI_IPC_HighValues = case_when(
+      is.na(rCSI)             ~ NA_integer_,
+      rCSI <= 3               ~ 1L,
+      rCSI >= 4  & rCSI <= 18 ~ 2L,
+      rCSI >= 19 & rCSI <= 42 ~ 3L,
+      rCSI >= 43              ~ 4L
+    ),
+    rCSI_IPC_HighValues = factor(
+      rCSI_IPC_HighValues,
+      levels = c(1,2,3,4),
+      labels = c("rCSI [0–3]  - IPC Phase 1",
+                 "rCSI [4–18] - IPC Phase 2",
+                 "rCSI [19–42] - IPC Phase 3",
+                 "rCSI [>42] - IPC Phase 4")
+    )
+  )
+
+table(df$rCSI_IPC_HighValues, useNA = "ifany")