1. www.mod.gu.se Weighting opt-in samples Some preliminary results from Sweden

2. www.mod.gu.se The Citizen Panel at LORE Respondents collected through VAAs in 2014: approx 30,000 Probability based recruitment to online panel through postcards: approx 10,000 Other various opt-in recruitments: approx 20,000

3. www.mod.gu.se Our strategy today We compare several data sources/samples: Basic demographics from Statistics Sweden (population register) The SOM Insitute postal probability survey (quasi benchmark) Our Citizen panel: Mixed opt-in recruitments Opt-in recruitments from 2014 VAA Probability based part of the panel

4. www.mod.gu.se Various possibilities for weighting and sample adjustments Various ways to adjust samples/panels to be representative (potentially) pre-stratification simple post-stratification (”multiplicative”, cell values/combinations unknown) ”raking” (iterative proportional fitting) post-stratification (”multivariate”/”cell based”) sample matching/propensity score matching

5. www.mod.gu.se Our data today Citizen panel wave from November/December SOM Insitute data from 2013 (2014 soon available) CP various opt-in: 10,555 responses CP VAA opt-in: 20,286 responses CP probability sample: 5,395 responses This wave included a larger set of variables with identical questions wordings as in other data sources

6. www.mod.gu.se About our two benchmarks Population register data the true benchmark (Statistics Sweden) But we mainly rely on a quasi benchmark, the SOM Institute surveys Annual mail survey with about 50 percent response rates based on the best possible sampling frame

7. www.mod.gu.se Some descriptive comparisons to the true benchmark

8. www.mod.gu.se Gender SwedenSOM MP-OI variousMP-OI VAMP-PROBMP-TOT Woman515238424842 Man494762575158 Other001101 Total100 Average absolute deviation from actual benchmark (percentage points)19626 Average absolute deviation from SOM benchmark (percentage points) 10737

9. www.mod.gu.se Age groups, 4 groups SwedenSOM MP-OI various MP-OI VA MP- PROBMP-TOT 18-29 years24161013912 30-44 years282432282329 45-59 years293334353334 60-70 years192724 3626 Total100 Average absolute deviation from actual benchmark (percentage points)675106 Average absolute deviation from benchmark (percentage points)5343

10. www.mod.gu.se Education SwedenSOM MP-OI variousMP-OI VAMP-PROBMP-TOT low16133454 medium low474314252321 medium high151114161516 high223363454850 Total100 Average absolute deviation from actual benchmark (percentage points)52215 17 Average absolute deviation from benchmark (percentage points)18111213

11. www.mod.gu.se Municipalilty size SwedenSOM MP-OI various MP-OI VA MP- PROBMP-TOT 1-29 999 inhabitants29 15242021 30 000-199 999 inhabitants51 43504647 200 000+ inhabitants20 43263432 Total100 Average absolute deviation from actual benchmark (percentage points)015498 Average absolute deviation from benchmark (percentage points)154108

12. www.mod.gu.se Some results Post-stratification weighting in three different ways

13. www.mod.gu.se First, we use the following variables: Age, gender, education, urbanisation Next, we also add how often they discuss politics

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20. Switching to comparing the different weighting strategies

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26. Conclusions Fewer cells or more fine grained post-stratification hardly makes any difference The probability panel benefits most from this basic weighting Basic demographic weighting doesnt help the opt-in samples much The real action happens when also weighting on a variable related to politics Different effects on different outcome variables

27. www.mod.gu.se Implications? Quasi benchmark is necessary Or, we need methods like raking, thus combining population register data with quasi benchmarks Or potentially other techniques such as sample matching for example