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Preparing Data for Import into SPSS
(Using Excel)
See
www.stattutorials.com/SPSSDATA
for files mentioned in this tutorial © TexaSoft, 2008
These SPSS statistics tutorials briefly explain the use and
interpretation of standard statistical analysis techniques for Medical,
Pharmaceutical, Clinical Trials, Marketing or Scientific Research. The examples
include how-to instructions for SPSS Software.
Preparing Data
for Import into SPSS (Using Excel)
Because creating
data in an Excel file is so common, this section discusses how you should
prepare your data in Excel (or any other spreadsheet or database program) for
importation into SPSS. Here are several items you should keep in mind.
-
Row 1 of your
Excel spreadsheet should contain variable names that are compatible with
SPSS naming conventions. Variable names should only be on row 1. Do not
extend names to row 2.
-
Variable
names must begin with a letter. Other characters allowed in the name
include any letter, any digit, a period, or the symbols @, #, _, or $.
Variable names cannot end with a period. Avoid names that end with an
underscore since that might conflict with internal SPSS variables.
-
Variable
names cannot exceed 64 characters.
-
Do not use
blanks or special characters (for example, !, ?, ', and *)
-
Variable
names must be unique; duplication is not allowed.
-
Do not use
reserved SPSS keywords as names. Keywords include:
ALL, AND, BY, EQ, GE, GT, LE, LT, NE, NOT, OR, TO, WITH.
-
Case does
not matter. Use any mixture of upper and lowercase characters when naming
your variable.
-
Each row
(line) in the Excel spreadsheet (other than the variable row) should
represent a single subject or observed entity.
-
Avoid blank
rows – it will complicate your import and analysis
-
If you have
missing data, do not leave that cell in Excel blank. Define a missing value
code and place that code in any cell that contains missing data.
-
Always use
date variables with 4 digit year formats in Excel. That is, enter date in
Excel using the format 01/01/2005 and not 01/01/05. Otherwise the old Y2K
problem can still be a problem for date calculations.
-
Use a data
dictionary to make sure to include all of the variables you need to
perform the tests you intend to perform. Use the specifications in the data
dictionary such as codes, formats and data ranges to define how you will
enter your data into Excel. Here is an example:
|
Variable Name |
Label |
Type (Width) |
Value Codes |
Missing Code |
|
ID |
Identification
Number |
String (4) |
none |
00000 |
|
Age |
Age on January 1,
2005 |
Numeric (3.0) |
none |
-9 |
|
Sex |
Gender |
Numeric (1.0) |
1=Female
2=Male |
-9 |
|
TDATE |
Test Date |
Date (10) (mm/dd/yyyy) |
none |
None |
|
SCORE |
Initial Test Score |
Numeric (6.2) |
None |
-9 |
-
If you have
the resources, enter your data twice (preferably using two different data
entry people) and compare the two files. This is a standard professional
practice that gives you added insurance that your data has been entered
correctly. It also helps to prevent the need to reanalyze your data when you
later realize that one or more entries were incorrectly coded into your
dataset.
-
Avoid putting
any extraneous text into your spreadsheet – put explanatory information in
other spreadsheets in the same file. Extraneous data in your primary
spreadsheet can make importing the data into SPSS more difficult.
Importing data
from Excel or other file formats
into SPSS
-
As
an example of what you're wanting, observe an Excel file that is prepared
for import into SPSS -- (In Excel, open the file named EXAMPLE.XLS –
see what it contains – then close it.)
-
Import
from Excel (EXAMPLE.XLS) (File/Open/Data, from “Files of Type” selection
box, select files of .xls type)
-
Check
the box labeled ‘Read variable name.’
-
Define
Sex variable types.
-
Change
ID to String.
-
Optionally
Save file as FROMLX.

See
www.stattutorials.com/SPSSDATA
for files mentioned in this tutorial © TexaSoft, 2008
End of tutorial
See
http://www.stattutorials.com/SPSS
Also, we recommend this book: Statistical
Analysis Quick Reference Guidebook: With SPSS Examples is a practical
"cut to the chase" handbook that quickly explains the when, where, and how of
statistical data analysis as it is used for real-world decision-making in a wide
variety of disciplines. In this one-stop reference, the authors provide succinct
guidelines for performing an analysis, avoiding pitfalls, interpreting results,
and reporting outcomes. Paperback. Sage Publishers ISBN:
1412925606
Order book from Amazon
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