![]() ![]() On the next line (new line not required, but recommended), type the number code that is currently in your data (to which you want to assign labels in my example, the first code is 1), followed by a space.On the next line (new line not required, but recommended), type the name of the variable you want to assign a value labels to (in my example, the variable is "Example1" see below).Type the command "VALUE LABELS" (be careful of spelling).Here are the steps to assign value labels (in the same syntax window): : if that is all you wish to do, start a new line and type EXECUTE, followed by another period If you want to also assign value labels, as we will here, you can save the EXECUTE until the end. On the same line as the variable name, insert a space, followed by a "single quote" (not a double quote/quotation mark), followed by whatever text you'd like to assign as the variable label for that variable, followed by another "single quote", and finally a period.On the next line (new line not required, but recommended), first type the name of the variable you want to assign a label to (in my example, the variable is "Example1" see below).Type the command "VARIABLE LABELS" (be careful of spelling).Open a new syntax window by clicking through the following menu path ( see below): File->New->Syntax. ![]() Here are the steps to assign variable labels: This is when syntax makes things MUCH easier! ![]() or 1000? Obviously, this can quickly turn into a ridiculously long process. That would work fine if you only have a couple of variables, However, what if you have 10 variables, or 20, or 100. In our example below, neither the variable labels (1) nor the value labels (2) have been assigned for any of our four example variables. To review, "data view" is used for editing the actual data, whereas "variable view" is used for editing the attributes of the variables (such as number of decimal places allowed, type of variable, the variable name, variable label, and value label). ![]() The screenshot below shows an example SPSS dataset I created for demonstration purposes (as you can see at the bottom of the screenshot, we are seeing the "variable view", as opposed to "data view". For example, "Gender" may be coded 0 (Males) and 1 (Females). Value Labels: Value labels are labels for coded variables in our dataset. If the variable labels are properly formatted in SPSS, they will show in output tables and graphs, instead of variable names. Variable Labels: Variable labels are composed of a few words that describe what a variable represents. When used in conjunction with the customizable SPSS table "Looks" function, formatting your variable labels and value labels can make your SPSS results tables nearly ready for publication, immediately after analysis! Fortunately, SPSS syntax offers a fairly straightforward method for assigning proper labels to both your variable labels and value labels.įor those of you unsure about the distinction between the two: Who among us have not been frustrated while wrestling with Microsoft Word? Unfortunately, that option only leaves additional opportunity for error and confusion, not to mention the inefficiency of editing tables in Microsoft Word. Besides recoding and cleaning variables, a diligent data analyst also must assign variable labels and value labels, unless they choose to wait until after your output is exported to Microsoft Word. Preparing a dataset for analysis is an arduous process. ![]()
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