Harmonisation of variables names prior to conducting statistical analyses with multiple datasets: an automated approach.

ABSTRACT:

Background

Data requirements by governments, donors and the international community to measure health and development achievements have increased in the last decade. Datasets produced in surveys conducted in several countries and years are often combined to analyse time trends and geographical patterns of demographic and health related indicators. However, since not all datasets have the same structure, variables definitions and codes, they have to be harmonised prior to submitting them to the statistical analyses. Manually searching, renaming and recoding variables are extremely tedious and prone to errors tasks, overall when the number of datasets and variables are large. This article presents an automated approach to harmonise variables names across several datasets, which optim

SUBMITTER: Bosch-Capblanch X 

PROVIDER: S-EPMC3123542 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature