@article {7574, title = {Automatic identification of variables in epidemiological datasets using logic regression.}, journal = {BMC Med Inform Decis Mak}, volume = {17}, year = {2017}, month = {2017 Apr 13}, pages = {40}, 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 were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated.

RESULTS: In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34\%, and a negative predictive value (NPV) of 95\%. In the validation sample, PPV was 33\%, whereas NPV remained at 94\%. In the construction sample, PPV was 50\% or less in 63\% of all variables, in the validation sample in 71\% of all variables.

CONCLUSIONS: We demonstrated that~the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies.

}, issn = {1472-6947}, doi = {10.1186/s12911-017-0429-1}, author = {Lorenz, Matthias W and Abdi, Negin Ashtiani and Scheckenbach, Frank and Pflug, Anja and B{\"u}lb{\"u}l, Alpaslan and Catapano, Alberico L and Agewall, Stefan and Ezhov, Marat and Bots, Michiel L and Kiechl, Stefan and Orth, Andreas} }