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Survey Design and Weighting Strategy for Mental Health of Children Study

This methodology outlines the survey design, weighting strategy, achieved sample, and selection process for studying the mental health of children and young people in 2017. It covers various aspects, including population, sampling frame, sample requirements, regional boosts, and weighting strategies.

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Survey Design and Weighting Strategy for Mental Health of Children Study

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  1. Sample Design and Weighting of the 2017 Mental Health of Children and Young People Survey Salah Merad Methodology Division, ONS Special thanks to Robynne Davies and Alexandra Pop RSS Social Statistics Section Event 12 February 2019

  2. Outline • Survey design • Weighting Strategy • Achieved sample

  3. Sample Design (1) • Population: Resident England population aged 2 to19 • Sampling Frame: NHS Patient Register (NHS Digital) • Child benefits records used in 2004 (5 to 16 years old) • Two-stage stratified design • Stage 1: selection of postcode sectors (explicit stratification by Region, implicit stratification by census factors (Social Renting, NSSEC, Unemployment) • Stage 2: selection of children from Patient register

  4. Sample Design (2) – Sample requirements • Achieve similar numbers to 2004 for 5 to 16 age group for England • Required achieved age distribution • Oversample children

  5. Sample Design (3) – Regional Boost • Reduce sample size variation across regions • Boost sample size of North East

  6. Sample Design (4) – Main and reserve samples • Assumed a response rate of 62% for 5 to 16 age group • In total, needed to select about 16,000 children from Patient Register • Selected a total of 379 postcode sectors, using probability proportional to size (PPS) within each region • Selected 42 children in each postcode sector using systematic PPS • Selected reserve sample using same design: 80 postcode sectors

  7. Sample Design (5) – Halls of residence • Initially intended to sample from university halls of residence to achieve about 100 interviews • Difficulty in accessing halls, so decided not to include them in sample

  8. Sample selection • Age was calculated as of August 31st 2017. • The target population is children born between and on the 1st September 1997 and 31st March 2015. • This was to ensure only those aged 2 before 1st April 2017 were included in the sample, and also to exclude those who turned 20 before the end of August 2017.

  9. Weighting strategy – Design weights • Design weights for main sample • PSU selection probabilities , • 2nd stage selection probabilities • 1/(product of selection probabilities) • Design weight for reserve sample

  10. Weighting strategy – Combining samples • Main and reserve samples combined together by assigning factors proportional to the respective samples sizes over the design effects stemming from weight variation • Design effect is given by • The combined weight was adjusted so that the distribution by Single Year of Age (age at interview) matches the distribution according to the population estimates.

  11. Weighting strategy – Non-response • Non-response factors were obtained by fitting a logistic regression model on the response indicator variable • Model covariates: the age used for sample selection(grouped), region (at selection), IMD and Urban/Rural indicators, and the source of the data (main or reserve sample) • Pre-calibration weight = Combined design weight/predicted probability

  12. Weighting strategy – Calibration to ONS population estimates • Separate calibration in each age group: (2-4, 5-9,10-15,16,17-19) • Calibration by sex and region within each group • Didn’t use data about the number of people in Higher Education, Further Education, Secondary education • Not easy to obtain an accurate estimate of HE students under 20 using data from HESA

  13. Distribution of final weights in age group 5 to 16

  14. Weighted sample: Distribution by ethnic group

  15. Design factor for Any Hyper Activity Disorder

  16. Weighting strategy – Teacher non-response adjustment • Teacher interview for 5 to 16 age group • Teacher’s score is combined with parents’ score to obtain clinical score • A proportion of children didn’t have a teacher interview • If teacher’s score is unavailable, clinical score is based on parents’ score only • Sampling weights were adjusted to compensate for lack of teacher’s scores

  17. Teacher non-response adjustment - Method • Calculate revised number of children with each clinically-assessed type of mental disorder in children with no teacher data • Adjustment factor given by

  18. Teacher adjustment factors for 5 to 16 year olds

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