Importing the Test Dataset

Lionel Jouffe; Stefan Conrady

Importing the Test Dataset into BayesiaLab

We show the first two steps of the Data Import Wizard only for reference, as their options have already been discussed in previous chapters.

Our test dataset consisting of 10,000 records was saved as a CSV file, so we start the import process via Menus > Data > Open Data Source > Text File.

Step 1: Data Structure Definition

Note the missing values in columns $\mathit{X1\_obs}$ , $\mathit{X2\_obs}$ , and $\mathit{X4\_obs}$ in the Data Panel. Column $\mathit{X5\_obs}$ features Filtered Values, which are marked with an asterisk (*).

Data Import step 1, Define Data Structure, listing the missing- and filtered-value markers alongside the data preview

Step 2: Definition of Variable Types

The next step of the Data Import Wizard requires no further input, but we can review the statistics provided in the Information Panel: we have 5,547 missing values (=11.09% of all cells in the Data panel) and 1,364 Filtered Values (=2.73%).

Data Import step 2, Define Variable Type, reporting 11.09 percent missing values and 2.73 percent filtered values

Step 3: Data Selection, Filtering, and Missing Values Processing

The next screen brings us to the core task of selecting the Missing Values Processing method. In the screenshot, the default option Structural EM is pre-selected, but we will explore all options systematically from the top. The default method can be specified under Menus > Window > Preferences > Data > Import & Associate > Missing & Filtered Values.

Data Import step 3 with the Missing Value Processing panel outlined in red

We explain and evaluate each Missing Values Processing method separately. Please select the topic below or open it in the navigation bar.

Generating the Test Dataset Infer — Dynamic Imputation