Note on weighting and a new weight variable in The Norwegian Citizen Panel

The Norwegian Citizen Panel uses weights to address known biases in the panel. We have now introduced a new weight variable, and we encourage all users of our data to use weight4 for their analyses.

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In the Norwegian Citizen Panel, respondents are randomly selected from the National Population Register, and participants are invited to participate via letters and SMS. To encourage participation, we randomly draw winners of travel gift cards each round. This random selection contributes to good representativity, but biases can still occur, especially over time. Therefore, we recommend using weights to address the known biases compared to the actual population related to education, gender, age, and region. In 2023, we have updated our weights, and all previous datasets have received a new weight, called Weight4. This is the weight we now recommend using in the analyses. It will be available in all NCP datasets over time, including those distributed by Sikt/Surveybanken.

Earlier, the weights were called weight1 and weight2. Existing datasets that had Weight1 and Weight2 will still have them, in addition to Weight4. In some rounds, you may also find Weight3 and Weight5, as these were weights we tested. From round 28 onwards, only Weight4 is available. This appears to be a well-functioning weight.

Weight4 is calculated as follows:

  • The weights are cell weights, calculated based on age (18-29 years, 30-59 years, 60+), gender (male/female), education (low (primary or secondary)/high (college or university)), and geography (regions). Population description is obtained from Microdata. This is as before in Weight2, but Weight4 splits the education variable into two instead of three.
  • The variable is capped (given a threshold value) to avoid weights stronger than 5 and weaker than 0.2. This is new in Weight4 and is to prevent individual participants from having too significant effects on analyses.
  • The weights are calculated using the entire dataset, so N = respondents in the dataset, even after weighting. This may result in less precision for some subgroups if, for various reasons, they are not distributed entirely randomly (usually not applicable). If necessary, you can calculate your own weights using Weight4_stratapop. This is as before in Weight2. Weight4_stratapop will be available in datasets from round 28, and we may also retroactively include it, if needed.
  • A few respondents have not provided information on education (e.g., 116 individuals in round 26). Therefore, a weight is also calculated with equivalent demographic variables but without education. Respondents lacking education information are assigned this weight. This is as before in Weight2.

Since this is new, we appreciate feedback if anything seems unusual with the weights.

Note! Even though the new codebooks now include weight4, they still contain an old text stating that weight2 is recommended. This is no longer accurate, as we now recommend weight4. The text will be updated at a later occation. Updated methodology reports documenting the change will also be available later.