Most real world data contain some (or many) missing values. It’s always a good idea to inspect the amount of missingness for avoiding unpleasant surprises later on. In order to do so, SPSS has some missing values functions that are mostly used with COMPUTE, IF AND DO IF. This tutorial demonstrates how to use them effectively. We’ll do so […]
SPSS AUTORECODE – Minimal Example autorecode str_var1 str_var2 str_var3 /into num_var1 num_var2 num_var3. Introduction This tutorial explains SPSS’ AUTORECODE command and shows how to use it properly on nominal_strings.sav, a screenshot of which is shown below. We recommend downloading this data file and following along with the steps in this tutorial. SPSS AUTORECODE – What Is It? […]
Summary SPSS uses a handful of hidden variables for keeping track of things. These so called system variables have names starting with “$” and can be useful in some cases. The most important one is $casenum, the number shown next to each case in the data editor window. SPSS $casenum SPSS $casenum In the left outline of the […]
5. Presence of User Missing Values (Overview and data file are are found here) User missing values are values that we want to exclude from analysis. We do so by specifying (ranges of) values as “missing” in SPSS. For ordinal variables, we typically exclude answers such as “Don’t know” or “Not applicable”. For metric variables, we exclude values that are not […]
SPSS System Missing Values SPSS User Missing Values Setting User Missing Values Inspecting Missing Values per Variable SPSS Data Analysis with Missing Values What are “Missing Values” in SPSS? In SPSS, “missing values” may refer to 2 things: System missing values are values that are completely absent from the data. They are shown as periods in data view. […]
