Working with Missing Values in the Codebook

You want to see some missing values ("missing values") in reports, but not others. Some missing values should be taken into account when calculating proportions, others should be excluded here. Instead of working with complicated workarounds, recodes or auxiliary variables, we in DataLion have provided extensive handling of missing values right from the start. You can define the different missing values or zero values and then either include or exclude them in calculations. This then also works in mean values or sums, so that a 99 is not used here as a number, but not counted at all.

Example:

• Missing Q1: 0
• Missing Q2: 99

Previously, missing values were defined at a project level and their handling was specified. Missing values can now also be defined and handled at a variable level via the codebook.

Now the following options can be added in the codebook in the "Settings" column:

• Exclude missing: {"na": "Item", "exclude_na":true}
• Include missing: {"na": "Item", "exclude_na":false}
• Several missing: "na": "Item1,Item2"

Important: When defining missings in the backend and in the codebook, the setting in the codebook has priority.