NCDS response and handling missing data

NCDS response

The table below presents statistics about response in the NCDS at every major sweep from birth. Take a look at our guidance for advice on handling missing data and restoring sample representativeness.

Of the 17,415 cohort members who participated in the first sweep, 4,497 (25.8%) have participated in all 11 sweeps. Of all 18,558 cohort members, 11,232 (60.5%) have taken part in 7 or more sweeps.

Table. Participation in the NCDS from birth to 55 years

Total cohort Dead Emigrants Eligible sample Participants (% of eligible sample)
Birth – 1958 17638 0 0 17638 17415 98.7
Age 7 – 1965 18016a 821 475 16720 15425 92.3
Age 11 – 1969 18287a 840 701 16746 15337 91.6
Age 16 – 1974 18558a 873 799 16886 14654 86.8
Age 23 – 1981 18558 960 1196 16402 12357 75.3
Age 33 – 1991 18558 1049 1335 16174 11469 70.9
Age 42 – 2000 18558 1199 1268 16091 11419 71.0
Age 44 – 2002 18558 1321 1234 16003 9377 58.6
Age 46 – 2004 18558 1323 1272 15963 9534 59.7
Age 50 – 2008 18558 1459 1293 15806 9790 61.9
Age 55 – 2013 18558 1659 1286 15613 9137 58.5

a The original sample was supplemented by migrants born in 1958

 

Handling missing data

Different types of people tend to drop out of our studies at different times, depending on their individual circumstances and characteristics.

To support researchers in producing robust analysis, we have developed comprehensive advice on how to deal with missing data.

The approaches we recommend to researchers capitalise on the rich data cohort members provided over the years before their non-response. These include well known methods such as multiple imputation, inverse probability weighting, and full information maximum likelihood.

Guidance on how users can adopt these methods for handling missing data in NCDS in their own analyses is available in our NCDS Missing Data User Guide.

We also offer training on handling missing data. Please keep an eye on our events page for details of future training. Or get in touch with us at ioe.clsevents@ucl.ac.uk.

In Mostafa et al[1], we show that the methods we recommend are able to restore the composition of the National Child Development Study (NCDS) samples at age 50 and age 55 to be representative of the study’s target population. For example, we were able to replicate the original distribution of paternal social class observed at the birth survey (see figure below), as well as the distribution of cognitive ability at age 7, and the known population distribution of educational attainment and marital status at age 50.

For further details, please see the resources on this website on handling missing data in all the CLS cohort studies.

 


Figure. Social class of mother’s husband at birth before and after adjustment for missing data.

Imputation phase of MI included predictors of response at age 55 and social class at birth only for cohort members that participated at age 55.

 


 

References

[1]  Mostafa, T., Narayanan, M., Pongiglione, B., Dodgeon, B., Goodman, A., Silverwood, R.J., and Ploubidis, G.B. (2020) Improving the plausibility of the missing at random assumption in the 1958 British birth cohort: A pragmatic data driven approach, CLS Working Paper 2020/6. London: UCL Centre for Longitudinal Studies.

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