By Sarah E. Boslaugh
An Intermediate consultant to SPSS Programming: utilizing Syntax for info administration introduces the main initiatives of information administration and offers strategies utilizing SPSS syntax. This publication fills a tremendous hole within the schooling of many scholars and researchers, whose coursework has left them unprepared for the knowledge administration concerns that confront them once they start to do self reliant examine. It additionally serves as an advent to SPSS programming. the entire simple gains of SPSS syntax are illustrated, as are many intermediate and complicated issues reminiscent of utilizing vectors and loops, examining complicated information documents, and utilizing the SPSS macro language.
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Extra resources for An Intermediate Guide to SPSS Programming: Using Syntax for Data Management
Data may be entered so multiple cases appear on one line, or a case may be spread over multiple lines. qxd 10/12/2004 3:52 PM Page 45 Reading Raw Data in SPSS 2. Because the FREE format defines variables by sequence rather than by column location, all variables must be defined in the order in which they appear in the file. 3. If a format is specified, it must include both the format name and variable width, as in the (A4) format for id in the above example. 4. If the blank space is used as a delimiter, it cannot also be used to identify a missing value.
Each row stores the information for one case, which in this example is one student. qxd 10/12/2004 3:52 PM Page 43 Reading Raw Data in SPSS Columns 1 through 4, the variable exam1 in Columns 5 through 7, the variable exam2 in Columns 8 through 10, and the variable exam3 in Columns 11 through 13. The first case has the id number 101 and grades of 97, 85, and 100 on the three exams. We could read this data into SPSS with the following syntax: DATA LIST / id 1-4 (A) exam1 5-7 exam2 8-10 exam3 11-13.
THE DEBUGGING PROCESS Writing well-organized programs makes the debugging process easier, as will the following suggestions: 1. Be familiar with the data set before you start testing your code. 2. Look at the results of each section of code to be sure they are what you expect: The LIST, FREQUENCIES, and CROSSTABS commands are particularly useful in this regard. This may be facilitated by running code on a subset of the active file, for instance, by using the SAMPLE command (discussed in Chapter 18).