Automatic identification of variables in epidemiological datasets using logic regression.

ABSTRACT:

Background

For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable.

Methods

For each variable in a set of target variables, a number of simple rules

SUBMITTER: Lorenz MW 

PROVIDER: S-EPMC5390441 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature