SDQ Predictive algoritm in R

Load required libraries

Note that the current scoring syntax is based on dplyr¹ which must be installed. I also recommend installing haven² to read SPSS files into R. Use the links to read more about dplyr and haven.

library(dplyr)
library(haven)

Load your data into R

The syntax is based on you reading you data into an object named sdq. This could be done with the command:

sdq <- read_sav("sdq.sav")

Note that read_sav is from haven and will fail if you have not installed it. Alternatively, you could use the package foreign, but this code is only tested with haven.

SDQ HYPERACTIVITY PREDICTION

sdq <- sdq %>%
  mutate(
    phk = case_when(
      phyper>=7 & pimpact>=2 ~ 2,
      phyper>=9 & pimpact>=1 ~ 2,
      phyper>=6 & pimpact>=1 ~ 1,
      phyper>=0 & pimpact>=0 ~ 0)
    )
 
sdq <- sdq %>% 
  mutate(
  shk = case_when(
    shyper>=7 & simpact>=2 ~ 2,
    shyper>=6 & simpact>=1 ~ 1,
    shyper>=0 & simpact>=0 ~ 0)
  )

sdq <- sdq %>% 
  mutate(
    thk = case_when(
      thyper>=7 & timpact>=2 ~ 2,
      thyper>=6 & timpact>=1 ~ 1,
      thyper>=0 & timpact>=0 ~ 0))
    

sdq$pshk <- sdq$phk
sdq$pshk <- ifelse(is.na(sdq$phk), sdq$shk, sdq$pshk)

sdq <- sdq %>% 
  mutate(
  sdqhk = case_when(
    pshk==2 & thk>=1 ~ 2,
    pshk>=1 & thk>=1 ~ 1,
    is.na(pshk) & thk>=1 ~ 1,
    pshk>=1 & !is.na(pshk) & is.na(thk) ~ 1,
    pshk==2 | thk==2 ~ 1,
    phk>=0 | shk>=0 | thk>=0 ~ 0)
  )

SDQ CONDUCT PREDICTION

sdq <- sdq %>% 
  mutate(
    sdqcd = case_when(
      is.na(pimpact) & is.na(timpact) & is.na(simpact) ~ NA_real_,
      pconduct>=5 & pimpact>=2 ~ 2,
      tconduct>=4 & timpact>=2 ~ 2,
      sconduct>=6 & simpact>=2 ~ 2,
      pconduct>=4 | tconduct>=3 | sconduct>=5 ~ 1,
      pconduct>=0 | tconduct>=0 | sconduct>=0 ~ 0)
    )

SDQ EMOTION PREDICTION

sdq <-  sdq %>% 
  mutate(
    sdqed = case_when(
      semotion>=6 & simpact>=1 ~ 1, 
      pemotion>=5 & pimpact>=1 ~ 1,
      temotion>=5 & timpact>=1 ~ 1, 
      pemotion>=0 | temotion>=0 | semotion>=0 ~ 0)
    )

sdq <- sdq %>% 
  mutate(pem = case_when(
         pemotion>=6 & pimpact>=2 ~ 1,
         TRUE ~ 0))

sdq <- sdq %>% 
  mutate(tem = case_when(
         temotion>=6 & timpact>=2 ~ 1,
         TRUE ~ 0))

sdq <- sdq %>% 
  mutate(sem = case_when(
         semotion>=7 & simpact>=2 ~ 1,
         TRUE ~ 0))

sdq <- sdq %>% 
  mutate(allem = pem + tem + sem)

sdq <- sdq %>% 
  mutate(
    sdqed_tmp = case_when(
      is.na(sdqcd) & is.na(sdqhk) ~ NA_real_,
      allem==1 & (sdqcd==2 | sdqhk==2) ~ 1,
      allem>=1 ~ 2, 
      sdqed==1 ~ 1,
      TRUE ~ 0))

sdq <- sdq %>% 
  mutate(
    sdqed = sdqed_tmp)

SDQ ANY DISORDER PREDICTION

sdq <- sdq %>% 
  mutate(
    anydiag = case_when(
      sdqed==2 | sdqcd==2 | sdqhk==2 ~ 2,
      sdqed>=1 | sdqcd>=1 | sdqhk>=1 ~ 1,
      sdqed>=0 | sdqcd>=0 | sdqhk>=0 ~ 0)
  )

CLEANING UP

# DELETE MIDWAY VARIABLES
sdq <- sdq %>% select(-phk, -shk, -thk, -pshk, -pem, -tem, -sem, -allem, -sdqed_tmp)

# ASSIGN LABELS
sdq$sdqhk   <- ordered(sdq$sdqhk,   levels = c(0, 1, 2), 
                       labels = c("Unlikely", "Possible", "Probable"))
sdq$sdqcd   <- ordered(sdq$sdqcd,   levels = c(0, 1, 2), 
                       labels = c("Unlikely", "Possible", "Probable"))
sdq$sdqed   <- ordered(sdq$sdqed,   levels = c(0, 1, 2), 
                       labels = c("Unlikely", "Possible", "Probable"))
sdq$anydiag <- ordered(sdq$anydiag, levels = c(0, 1, 2), 
                       labels = c("Unlikely", "Possible", "Probable"))

Download R script.