An Assessment of the Young Lives Sampling Approach in Andhra Pradesh, India
Young Lives is a longitudinal research project investigating the changing nature of childhood poverty. The study is tracking the development of 12,000 children in Ethiopia, Peru, India (Andhra Pradesh) and Vietnam through qualitative and quantitative research over a 15-year period. Since 2002, the study has been following two cohorts in each study country. The younger cohort consists of 2,000 children per study country aged between 6 and 18 months in 2002. The older cohort consists of 1,000 children per country aged between 7.5 and 8.5 in 2002. The key objectives of Young Lives are: (i) to improve the understanding of causes and consequences of childhood poverty, (ii) to inform the development and implementation of future policies and practices that will reduce childhood poverty.
The sampling methodology adopted by the Young Lives team in Andhra Pradesh is known as a sentinel site surveillance system. It consisted of a multi-stage, purposive and random sampling to select the two cohorts of children. This methodology randomised households within a study site while the sites themselves were chosen on the basis of predetermined criteria, informed by the objectives of the study. To ensure the sustainability of the study, and for resurveying purposes, a number of well-defined sites was chosen. The sites were selected from three different agro-climatic areas and, in accordance with the project aims, had a pro-poor bias ith districts and sites being ranked according to a number of development indicators.
This paper assesses the sampling methodology by comparing the Young Lives sample with a larger, nationally representative sample. In doing this, the Andhra Pradesh team sought to:
analyse how the Young Lives children and households compare with other children in India in terms of their living standards and other characteristics; examine whether this may affect inferences between the data; establish to what extent the Young Lives sample is a relatively poorer or richer sub-population in Andhra Pradesh; determine whether different levels of living standards are represented within the dataset.