Understanding Society User Support

Hi Akansha,

To link youth to themselves across waves, use their PIDP. To link to their parents, the easiest way is to use the identifiers of parents available in the youth file based on PIDP:

o_fnpid — Natural father: PIDP
o_mnpid — Natural mother: PIDP
o_pn1pid — Natural parent 1: PIDP
o_pn2pid — Natural parent 2: PIDP
o_pns1pid — Nat/step/adopt parent 1: PIDP
o_pns2pid — Nat/step/adopt parent 2: PIDP

For each youth respondent, this variable gives you their parent’s PIDP.
For example, if there was a youth respondent identified by PIDP=234572 in Wave 15, then in Wave 13 this PIDP=234572 identifies the same youth respondent/child (in any relevant file, not only w_youth, of course assuming that they were enumerated and completed a given interview in this wave). If, for this youth respondent (PIDP=234572), o_fnpid=98890, then this means that the respondent identified by PIDP=98890 is their natural father; this will apply to any other individual-level file, not only indresp (again, subject to their participation, eligibility and interview completion).

To learn more about linking household members, I recommend:

1. checking worksheets 7 and 8 in our Moodle course (https://www.understandingsociety.ac.uk/help/training/introduction-to-understanding-society-self-paced-moodle/
),

2. checking this forum for similar questions, as some of these include syntax files posted by us and may be useful,

3. checking our syntax website (https://www.understandingsociety.ac.uk/documentation/mainstage/syntax/
), particularly “Matching individuals within a household” and “Matching co-resident parents’ information”

I hope this helps,

Best wishes,
Piotr Marzec
UKHLS User Support

Hi Akansha,

I see. Adresp15_dv give you the person number of person responsible for child under 16, that is, their PNO variable value. PNO in combination with HIDP can be used as a unique identifier within one wave. You can also easily get the PIDP of each person knowing the combination of their PNO and HIDP. A simple R code doing such a merge which links the responsible adult highest level of education earned to youth respondents would look like this (it uses inner_join so only youth respondents with valid adresp15_dv and matches in indresp are left):

library(tidyverse)
library(haven)
# Define paths
path2 <- "C://Main/stata/Nov25/UKDA-6614-stata/stata/stata14_se/ukhls" 

# Load youth data
o_youth <- read_dta(file.path(path2, "o_youth.dta"))

# Count observations
cat("Number of observations:", nrow(o_youth), "\n")

# Rename variables for the merge to work
o_youth <- o_youth %>%
  rename(
    o_pno_org = o_pno,
    o_pno = o_adresp15_dv
  )

# Load indresp - selecting only hiqual_dv columns plus merge keys
o_indresp <- read_dta(
  file.path(path2, "o_indresp.dta"),
  col_select = c(o_pno, o_hidp, ends_with("hiqual_dv")))

# Merge (inner_join replicates keep if _merge==3)
# Since you want m:1 and keep only matched, inner_join is appropriate
o_youth_merged <- o_youth %>%
  inner_join(o_indresp, by = c("o_pno", "o_hidp"))

# Verify count after merge
cat("Number of observations after merge:", nrow(o_youth_merged), "\n")

I again recommend checking worksheets 7 and 8, and the fragments of the Getting started workshop related to merging partner info as a similar logic applies to any other merges.

The adresp15_dv in the waves you are interested is created as follows:

Step 1: Create adresp15_dv
gen ${wave}adresp15_dv = -9
• Creates the variable and sets everyone to -9 (initially “missing”).

Step 2: Identify children (and child-like cases when age is missing)
gen age015 = (inrange(${wave}age_dv, 0, 16))
gen iout015 = (inlist(${wave}ivfio, 21, 22, 23, 24, 25, 63))
• A flag age015 = 1 if the person is aged 0–16 (treated as a child in this logic).
• A flag iout015 = 1 if the interview outcome (ivfio) is one of 21–25, 63.
• Together, these allow the code to treat someone as a “child case” either because:
o they are aged 0–16, or
o age is missing/negative but the interview outcome suggests a youth/child outcome.

Step 3: Mark adults as “inapplicable”
replace ${wave}adresp15_dv = -8 if (age015 ~= 1) & (iout015 ~= 1)
• If someone is not a child by age and not flagged by the child-related ivfio outcomes, set adresp15_dv to -8 (“inapplicable”).
• Rationale: adults don’t need a “responsible adult” assigned.

Step 4: Assign the responsible adult for children using a hierarchy of pointers
• For those treated as child cases (age015==1 or age_dv<0 & iout015==1), the programme assigns adresp15_dv to a positive person number (PNO) by checking caregiver pointers in a fixed priority order.
• It starts with natural mother, then natural father, then step-parents, then foster parents, then grandparents, only moving down the list if no valid positive PNO has been assigned yet.
Priority order used: Natural mother → 2) Natural father → 3) Step-mother → 4) Step-father → 5) Foster mother → 6) Foster father → 7) Grandmother → 8) Grandfather

In waves <= there was also a fallback based on adresp15 (https://www.understandingsociety.ac.uk/documentation/mainstage/variables/adresp15/). I'm attaching the full code creating adresp15_dv.

I hope this helps.

Best wishes,
Piotr Marzec
UKHLS User Support