Presentation on theme: "The English Longitudinal Study of Ageing (ELSA) Sample design & response Shaun Scholes NatCen."— Presentation transcript:
The English Longitudinal Study of Ageing (ELSA) Sample design & response Shaun Scholes NatCen
Content Presentations on weighting are incredibly dull (!) so: A focus on sample design: Who’s included? Who’s excluded and why? A brief analysis of response by Wave 3 (for those who took part at Wave 1): Who remains? Who drops-out?
Sample design (1) – Eligibility (core members) Include if belong to ELSA’s target population: Persons aged 50+ (age-eligibility) Living in private households in England (wave 1) and Great Britain (subsequent waves) –Institutional interviews Partners interviewed but not of interest in themselves: –‘End-of-life’ interview –Understand circumstances of couple –Understand circumstances after ‘split’
Sample design (2) – issued for fieldwork Being eligible (i.e. in target population) does not guarantee being issued for fieldwork Respondents at HSE/each ELSA wave could have refused permission to be re-contacted: BUT we use a household rather than individual definition Individual ‘refusers’ still have an opportunity to take part if another eligible person in the household did not refuse re-contact
Origin of the ELSA sample ELSA is a follow-up of Health Survey for England responding households: Benefits of follow-up: –Nationally representative of private households –Identify eligible individuals at reasonable cost –Wide range of information already collected –Respondents took part in survey already so more likely to take part in new survey Disadvantages of follow-up: –Initial non-response –Refusals to be re-contacted for further study –Drop-out between initial and follow-up survey
Composition of ELSA sample Determined by: Being in a responding HSE HH Eligibility: –Age (Cohort 1 core members born before 1 March 1952) –Living in private household in England at time of wave 1 –Being a partner of sample member Whether issued for fieldwork: –Age-eligible person in HH agreeing to further contact post HSE Propensity to respond conditional on being issued: –Household level non-response –Individual level non-response within responding households –Item/module non-response Self-completion questionnaire (all waves) Income information (all waves) Nurse visit and blood sample (waves 2 & 4)
Response tree from wave 1 to wave 2 CM Core member CP Core partner YP Young partner NP New partner (entering study at waves 1 and/or 2) Stage 1 All HH containing at least 1 CM, YP or NP responding in wave 1 7,934 households Stage 2 HH not issued 343 households HH issued 7,591 households New HH formed 34 households Stage 3 Ineligible HH 175 households Responding HH 6,277 households Non-responding HH 1,173 households Stage 4 Responding individuals 9,433 CM = 8,781 CP = 57 YP = 501 NP = 94 Non-responding individuals 420 CM = 120 CP = 215 YP = 44 NP = 41 Ineligible individuals 227 CM (deaths) = 181 CM (institutional moves) = 14 CP = 7 YP = 25
Response over three waves Focus here on Cohort 1 core members (took part at wave 1) The next slide shows, at each wave, the number of: R ~ Respondents NR ~ Non-respondents –refusals –Non-contacts –Unable to trace –‘Other’ (e.g. ill/away during fieldwork) I ~ Ineligible cases (known ineligibility)
11,391 8,780 (82%) 7,168 (86%) 1,191421 1,989 314 (17%) 1,507168 621 621517 R NR I W1 W2 W3
Non-response Non-response causes two problems for longitudinal surveys (Uhrig, 2008): Lower sample size results in lower precision Non random non-response means sample becomes unrepresentative as the longitudinal sample ages. Bias exists when the R and NR vary with respect to outcomes Advantage of panel surveys (compared to cross- sectional ones) is that we have survey data collected at the first wave (Lynn, 2008) to compare R and NR - and use for weighting.
Predictors of non-response Four groups of eligible cases are compared across selected W1 variables: XXX (took part in all 3 waves) XXO (dropped out after W2) XOX (returned at W3 after missing W2) XOO (dropped out after W1) All wave 1 respondents used as the benchmark. If NR = random all distributions would equal the W1 distribution (Lynn et al., 1994) Hypothesis: XXX = most educated/affluent, younger, healthier XOO = least educated/affluent, older, poorer health XOX/XXO = somewhere in between
Conclusions Many steps to go through to have been selected for the ELSA sample and to have taken part in all three waves. Be aware of the existence of different cohorts as time progresses. Be critical/cautious about the types of respondents who remain - a random subset of the target population? Probably not.
References Lynn P (2008) ‘Non-response’ in E.De. Leeuw, J.J. Hox and D.A. Dillman International Handbook of Survey Methodology (New York: Lawrence Erlbaum Associates). Lynn, P., Purdon, S., Hedges, B. and McAleese, I. (1994), The Youth Cohort Study: An Assessment of Alternative Weighting Strategies and their Effects, Employment Department Research Series YCS. Report no.30. Uhrig, S.C. Noah (2008) ‘The nature and causes of attrition in the British Household Panel Survey’, Working Papers of the Institute for Social and Economic Research, paper 2008-05. Colchester: University of Essex.
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