Comment and minor changes

R/fun_generate_gambles.R

+# Function for generating 2-outcome gambles
+## n: number of gambles
+## safe: gamble typ; TRUE = safe vs. risky option; FALSE = risky options only
+## lower, upper: lower and upper boundary of outcome range
+
 generate_gambles <- function(n, safe = TRUE, lower, upper) {
 
-  # n: number of gambles
-  # safe: gamble typ; TRUE (default) = safe vs. risky option; FALSE = risky options only
-  # lower, upper: lower and upper boundary of outcome range
+  # define a function for computing expected values
 
   ev <- function(p1, o1, o2 = 0) {
-    round(p1 * o1 + (1-p1) * o2, digits = 2) # expected value for n <= 2 outcomes
+    round(p1 * o1 + (1-p1) * o2, digits = 2)
   }
 
   output <- vector("list", n)
 
+  # safe vs. risky gambles
+
   if(safe == TRUE) {
 
-    # safe vs. risky gambles
+    # for each gamble, randomly draw outcomes and probabilities
 
     output %>%
-      map(tibble, # create tibble for each gamble/list entry
-          "names" = c("a_o1", "b", "a_o2", "a_p1", "b_p"),
-          "values" = c(runif(3, min = lower, max = upper) %>% round(2) %>% # generate outcomes
-                         sort(), # prevent dominance: a_o1 < b < a_o2
-                       runif(1, min = .01, max = .99) %>% round(2), # probabilities
-                       1)
-      ) %>%
-      map(pivot_wider, names_from = "names", values_from = "values") %>% # tidy: gambles as obs (rows)
-      map_dfr(as.list) %>% # return tibble including all gambles (row-binding)
-      mutate(a_ev = ev(a_p1, a_o1, a_o2),
-             b_ev = ev(b_p, b),
+      map(tibble, # create tibble for each gamble
+          "names" = c("a_o1", "b_o1", "a_o2", "a_p1"), # randomly generated values
+          "values" = c(runif(3, min = lower, max = upper) %>%  # outcomes
+                         round(2) %>%
+                         sort(),
+                       runif(1, min = .01, max = .99) %>% # probabilities
+                         round(2))
+          ) %>%
+
+      # each gamble should be presented in a single row
+
+      map(pivot_wider, names_from = "names", values_from = "values") %>%
+      map_dfr(as.list) %>%
+
+      # add gamble features that are determined by the random samples from above
+      # compute and compare expected values
+
+      mutate(a_p2 = 1-a_p1,
+             b_o2 = 0,
+             b_p1 = 1,
+             b_p2 = 0,
+             a_ev = ev(a_p1, a_o1, a_o2),
+             b_ev = ev(b_p1, b_o1, b_o2),
              ev_diff = round(a_ev - b_ev, 2),
              ev_ratio = round(a_ev/b_ev, 2)
       ) %>%
-      select(a_p1, a_o1, a_o2, a_ev, b_p, b, b_ev, ev_diff, ev_ratio)
+      select(a_p1, a_o1, a_p2, a_o2, b_p1, b_o1, b_p2, b_o2, a_ev, b_ev, ev_diff, ev_ratio) # sort features
 
   } else {
 
@@ -39,18 +56,20 @@ generate_gambles <- function(n, safe = TRUE, lower, upper) {
       map(tibble,
           "names" = c("a_o1", "b_o1", "a_o2", "b_o2", "a_p1", "b_p1"),
           "values" = c(runif(3, min = lower, max = upper) %>% round(2) %>%
-                         sort(), # prevent dominance: a_o1 < b_o1 and/or b_o2 < a_o2
-                       runif(1, min = lower, max = upper) %>% round(2),
+                         sort(), # prevent dominance: a_o1 < b_o1 < a_o2
+                       runif(1, min = lower, max = upper) %>% round(2), # b_o2
                        runif(2, min = .01, max = .99)
           )
       ) %>%
       map(pivot_wider, names_from = "names", values_from = "values") %>%
       map_dfr(as.list) %>%
-      mutate(a_ev = ev(a_p1, a_o1, a_o2),
+      mutate(a_p2 = 1-a_p1,
+             b_p2 = 1-b_p1,
+             a_ev = ev(a_p1, a_o1, a_o2),
              b_ev = ev(b_p1, b_o1, b_o2),
              ev_diff = round(a_ev - b_ev, 2),
              ev_ratio = round(a_ev/b_ev, 2)
       ) %>%
-      select(a_p1, a_o1, a_o2, a_ev, b_p1, b_o1, b_o2, b_ev, ev_diff, ev_ratio)
+      select(a_p1, a_o1, a_p2, a_o2, b_p1, b_o1, b_p2, b_o2, a_ev, b_ev, ev_diff, ev_ratio)
   }
 }