For merging SPSS data files with similar cases but different variables, use MATCH FILES. Make sure your case identifier -if any- doesn’t contain duplicate values and the files are sorted ascendingly on it. The result contains all cases from both files (like a full outer join in SQL).Second, MATCH FILES also performs a table lookup as illustrated below. SPSS […]
SPSS FORMATS sets formats -decimal places, dates, percent signs and more- for numeric variables. Setting variable formats in SPSS does not change your actual data values. However, formats determine how your data are displayed -in the data viewer as well as the output-window. Two main uses of FORMATS are increasing or decreasing the decimal places of standard numeric variables; displaying date, time and datetime values (consisting […]
Cramér’s V is a number between 0 and 1 that indicates how strongly two categorical variables are associated.If we’d like to know if 2 categorical variables are associated, our first option is the chi-square independence test. A significance level close to zero means that our variables are very unlikely to be completely unassociated in some population. However, this does not […]
An often requested feature is to export variable and value labels to Excel. This handy tool creates an SPSS Dataset containing these labels. It can either be be saved as an Excel sheet or further edited in SPSS. SPSS Create Dictionary Dataset Tool – How To Use Make sure you have the SPSS Python Essentials installed. Next, download and […]
SPSS doesn’t offer an easy way to set decimal places for output tables. This tutorial proposes a very simple tool for setting decimal places in basic output tables after they’ve been produced. It works best for simple tables such as DESCRIPTIVES, MEANS or CROSSTABS. Setting Decimal Places for Output Tables First, make sure that the SPSS Python Essentials are installed and […]
9. Missing Values per Case (Overview and data file are are found here) Missing values complicate some analyses or may sometimes indicate that respondents didn’t fill out the questionnaire very seriously. In any case, it’s a good idea to at least check how missing values are distributed over respondents and we often do so for sections […]
6. Inconvenient Distributions (Overview and data file are are found here) Let’s first state this clearly: we don’t exclude variables simply because their distributions are not to our liking. What we mean by “inconvenient distributions” are variables that don’t really provide us with useful information. This point is perhaps best explained by an example. Let’s inspect q4. […]
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 […]
MATCH FILES is an SPSS command mostly used for merging data holding similar cases but different variables. For different cases but similar variables, use ADD FILES. MATCH FILES is also the way to go for a table lookup similar to VLOOKUP in Excel. Merging two datasets by id, which is a unique case identifier. SPSS Match Files – Basic Use The […]
For converting string variables to date variables, ALTER TYPE is the way to go. This tutorial demonstrates how to do this and points out a couple of caveats. For those who can’t use ALTER TYPE, we’ll propose some alternatives. SPSS Alter Type The syntax below first creates a mini dataset holding 8 string variables. They demonstrate the 8 most common date formats. Next, […]
By default, every case in your data counts as a single case. However, you can have each case count as more or less than one case as well. This is called weighting. For instance, the first case in your data may count as 2 cases and the second one as .5 cases. These numbers, the case weights, […]
