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Outline of talk The ONS surveys Why should we weight?

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Presentation on theme: "Outline of talk The ONS surveys Why should we weight?"— Presentation transcript:

1 Weighting on National Statistics Household Surveys Jeremy Barton Office for National Statistics

2 Outline of talk The ONS surveys Why should we weight?
The weighting process When should we use weights?

3 ONS social surveys Labour Force Survey (LFS)
General Household Survey (GHS) Expenditure & Food Survey (EFS) Family Resources Survey (FRS) Omnibus Survey (OMN)

4 Labour Force Survey Quarterly panel survey (c. 56K hh per qtr)
HHs stay in survey for 5 qtrs require estimates of: totals (e.g. employment) rates (e.g. unemployment) interview: all hh members Local boosts for annual estimates

5 General Household Survey
9,000 hhs per annum housing, consumer durables, employment, health, family structure, pensions, education also ad hoc trailers, e.g. drinking interview: all hh members

6 Expenditure & Food Survey
Merger of Food and Expenditure surveys 7,000 HHs in UK 14 day expenditure diary Expenditure and income Food consumption and nutrient intake Interview: all hh members

7 Family Resources Survey
For DWP 25,000 HHs per year Income, benefits, pensions, savings Fieldwork shared by ONS and NatCen HHs, individuals, benefit units Interview: all hh members

8 Omnibus Survey Interview: 1 adult per hh 1,800 adults per month
Core questionnaire and modules Covers a great range of different topics

9 Why should we weight? Adjust for unequal selection probabilities
Adjust for nonresponse Adjust our sample to match known population totals

10 Probability weights Weight µ 1/(prob of selection) Boost samples
EFS in NI, weight = GB weight /4 more common in ad hocs

11 Probability weights Subsampling of units Omnibus (1 adult per hh)
weight = # adults in hh FRS (Multi-household addresses)

12 Nonresponse weights

13 Nonresponse weights Sample-based nonresponse methods
Split set sample into weighting classes Estimate weighted response rates in each class New weight is 1/RR

14 Nonresponse weights Response rates different in each weighting class
Means for major survey variables must differ between each class Means for major survey variables must be same for R and NR within each class

15 Nonresponse weights GHS and EFS Based on Census-link studies 1991
Target nonresponse in specific demographic groups Sampling frame information Interviewer observations

16 EFS NR weighting classes

17 Population weights LFS Mar-May 2003

18 Population weights Produce population totals of estimates
Reduce nonresponse bias further Improve precision (reduce SEs) Comparability across surveys a.k.a. calibration, post-stratification

19 LFS Population weights
LFS - Individual level weights raking to 3 controls: 5 yr age group by sex within region Local Authority Single years by sex population projections

20 LFS Population weights
LFS HH level weights Same weight each hh member (Lemaitre/Dufour) software: Calmar bounded weights Age group 5 yrs and single years by sex and region

21 GHS/EFS Pop. weights HH-level weights Pre-weighted by NR/prob weights
Calibrate to 5-year age groups by sex and to region Pop estimates excl. communal establishments

22 FRS Population weights
Calibration to: Age group, sex, marital status Lone Parents Families Tenure Type Council Tax band Region

23 The weighting process EFS 2001/02

24 When to use weights Always (whenever you can)
Problems with presentation /interpretation estimates / sample sizes / SEs NR & probability weights tend to increase variances

25 When to use weights Stat packages (e.g. SPSS) don’t always deal with weighting correctly Scale weights to average 1 Stata/SAS survey estimation procedures Calibration tends to reduce variances

26 Conclusions Weights combination of probability, NR, calibration
Required for unbiased estimation May require specialist software for correct hypothesis testing

27 Current Issues Use of 2001 Census data Census-linked NR studies
Change in Pop. Controls (back-weighting) Integrated survey (CPS) LFS: Attrition weighting Local LFS Number of controls

28 References Weighting for non-response, Elliot, D. NM17
Grossing Up - when and how, Butcher, B. SMB 14 The presentation of weighted data in survey report tables, Elliot, D. SMB 38 Using weights in regression analysis: A comparison between SPSS and STATA packages, Insalaco, F. SMB 45 Developing a weighting and grossing system for the GHS, Barton, J. SMB 49 Evaluation nonresponse on household surveys, Foster, K. GSS Methodology Series 8. Report of the Task Force on Weighting and Estimation, Elliot, D. GSS Methodology Series 16.

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