您有匹配ptid/num/type/time的观测。如果您希望它们是单独的行而不是该位置的列表，请添加一个标识符以区分它们：

df %>%
  dplyr::mutate(iteration = dplyr::row_number(), .by = c(ptid:time)) %>%
  pivot_wider(names_from = c("time", "type"),
              values_from = "volume",
              names_prefix = "time",
              names_sep = "")

# A tibble: 6 × 9
   ptid   num iteration time1type1 time2type1 time3type1 time1type2 time2type2 time3type2
  <int> <int>     <int>      <dbl>      <dbl>      <dbl>      <dbl>      <dbl>      <dbl>
1     1     1         1     0.0202       1.09      -1.72      NA        NA         NA    
2     1     1         2    -0.473       NA         NA         NA        NA         NA    
3     1     2         1    NA           -1.06      -1.02      NA        NA         NA    
4     2     2         1    NA           NA         NA         -1.11     -0.494     NA    
5     2     3         1    NA           NA         NA         -1.34     -0.146     -1.08 
6     2     3         2    NA           NA         NA         NA        NA         -0.463

library(dplyr)
library(tidyr)

df %>% 
  unite(time_type, c(time, type), sep = "") %>% 
  pivot_wider(names_from = time_type,
              values_from = volume,
              names_prefix = "time", 
              values_fn = list) %>% 
  unnest(cols = c(time1type1, time2type1, time3type1, time1type2, time2type2, time3type2))

ptid   num time1type1 time2type1 time3type1 time1type2 time2type2 time3type2
  <int> <int>      <dbl>      <dbl>      <dbl>      <dbl>      <dbl>      <dbl>
1     1     1      0.864     -1.02       0.577     NA         NA         NA    
2     1     1      1.33      -1.02       0.577     NA         NA         NA    
3     1     2     NA         -0.909     -1.30      NA         NA         NA    
4     2     2     NA         NA         NA          0.255     -0.549     NA    
5     2     3     NA         NA         NA         -0.213      0.139     -1.59 
6     2     3     NA         NA         NA         -0.213      0.139     -0.384