A wave consists of a 24-monthly samples with participants interviewed at regular 1-year intervals.
As some samples are fielded in the first 12 months (BHPS and the GPS-NI, GPS2-NI samples), some in months 13-24 (IEMB sample) and some across all 24 months (GPS-GB, GPS2-GB and the EMB samples), just using data from the same wave to compare the two consecutive years will result in comparing different samples (see the Study design for details on each sample). Similarly, just using data from year 1 or year 2 of a wave to conduct cross-sectional analyses of that year will result in analysing samples that are not-representative. So, to correctly do these types of analyses, data from two waves need to be combined. For example, for 2019, use data from year 2 of Wave 10 and year 1 of Wave 11.
To make this process easier we have created a ready prepared calendar year dataset containing data for a whole year under a separate study number starting with the calendar year dataset for 2020 released in early 2022. A user guide accompanies the dataset which contains data from the second year of data collection for Wave 11 and data collected in the first 12 months of fieldwork for Wave 12. This dataset is not intended for longitudinal use and is for cross-sectional use only. It contains core questions but also the rotating modules (i.e., modules only asked in Wave 11 and some only asked in Wave 12). Note the 2019 calendar year data have been released with the COVID-19 Survey data and contain the second year of Wave 10 and first year of Wave 11.
The new cross-sectional calendar year datasets are planned for each subsequent year and will contain data from the second year of one Wave and early release of the first year of the next Wave. For example data from the year 2022 would contain data from the second year of data collection for Wave 13 and (at the time) early release of the data already collected in the first 12 months of fieldwork for Wave 14. If you would like to analyse yearly data for years prior to 2019, you can produce calendar year datasets by combining data collected in a specific year from all relevant waves which were being fielded in that year. For example, for the 2012 dataset, combine data from Waves 2, 3 & 4 by selecting cases who were interviewed in 2012.
