At this stage of model development, the covariate structure of the model is reconstructed in an automated way. This is the last step of the binary exposure-response model development.

There are two panels on this page:

  • General panel contains inputs for the necessary information for the covariate search
  • Options panel contains inputs with options of the covariate search algorithm

General panel

On General panel the way to the working directory should be provided to the interface. It is done by the Source input. This input has two options. The first one is . If this option is chosen, the working directory will be equal to the one chosen on the Data Initialization panel. Another option is . After choosing this option the user can specify any project folder by pressing on .

For the proper work of the algorithm, the chosen folder should contain the file LogitModelsList.RData with the list of base models for each response variable. The path to the chosen directory is printed in the interface. Also, response variables, exposure metrics and covariates should be specified on the Data Initialization panel.

After inputting all necessary information, the user can press button to start the covariate search algorithm. After the search is finished, the table with best models for each of the provided base models will be printed in the interface. The table will contain the following information:

  1. Final Model Structure:

    • Response The endpoint variable described by the model.

    • Exposure The exposure metric that best characterizes the response variable.

    • Covariates Statistically significant covariates included in the model.

  2. Information Criteria Values:

    • LL The log-likelihood of the fitted model.

    • AIC Akaike Information Criterion values.

  3. Change in Information Criteria:

    The difference in LL and AIC values compared to the corresponding base model.

The user can save this table to the working directory by pressing button. Also, the user can save the list of final models to the working directory by pressing the button.

General Tab Screen

Options panel

The covariate search is performed using stepwise procedure. It consists of two parts: forward selection and backward elimination. On the options tab the parameters of the algorithm can be adjusted. The user can change the metric used for model comparison by Covariate evaluation method input. There are two options: model comparison with log rank test ( option) and Akaike information criterion ( option). In accordance with the chosen evaluation metric, thresholds for forward selection and backward elimination can be changed.