Presentation on theme: "Melissa Davy Office for National Statistics"— Presentation transcript:
1 Melissa Davy Office for National Statistics Pseudo-cohort analysis - trends in smoking data using the General Household SurveyMelissa DavyOffice for National Statistics
2 Introduction Why we carried out pseudo cohort analysis (PCA) The advantages and disadvantagesThe survey we used in our analysisThe methods we usedWork through an example
3 Why is it useful to look at cohort analysis? Interested in inequalities over time and by birth cohortPeople in different birth cohorts have different experiencesCohort analysis provides a better understanding of how events change over time
4 What is pseudo-cohort analysis? - panel data- same individualPseudo-cohort analysis- cross-sectional data- average experience of a given cohortFor example- aged 20 to 25 in a 1980 survey= 21 to 26 in 1981= 22 to 27 in 1982= 44 to 49 in 2004.
5 Advantages of pseudo-cohort analysis Uses data that are already availableNew sample each year so no problem of non-random attritionLess burden on respondentsMore frequent data
6 Disadvantages of pseudo-cohort analysis Variations in the nature of the samples surveyedLooking at average experience of the cohort limits the use of the dataRecall biasNot straightforwardSmall cell sizes
7 General Household Survey Dataset goes back more than 30 yearsThe GHS covers a range of topicsRelatively large sample sizeHigh quality data source
8 Extracting the data– create a database which includes all survey years– create a birth cohort variableDisadvantages- Time consumingAdvantagesValuable research toolExploiting full potential of the GHS dataMakes time series analysis easier
9 Creating the dataset Long process documented in: Uren Z (2006) The GHS Pseudo Cohort Dataset (GHSPCD): Introduction and Methodology. Survey Methodology Bulletin, no 59, pp25-37.Available at:contains over 40 variables,records for over 800,000 individuals.
10 The smoking example Analysis of smoking among men trends over time trends by agepseudo-cohort analysis- interaction of time and age
24 Main findingsAt every age, men smoke less than the previous generation.Not due to established smokers giving up more rapidlyIn the most recent cohorts- fewer men were starting to smokebut were then giving up at a slower rate than in the past.Smoking prevalence rates may be stabilising.
25 ConclusionPseudo-cohort analysis gives us a better understanding of the GHS smoking data