![]() IBM's technical support resource for all IBM products and services including downloads, fixes, drivers, APARs, product documentation, Redbooks, whitepapers and technotes. Finding the Jack Number on a Wall Plate. If you need more than one SPSS license, please contact the help desk at [email protected] and briefly explain why you need. ![]() Do you need SPSS help? SPSS is an IBM creation and stands for the Statistical Package for the Social Sciences. SPSS is an IBM creation and stands for the Statistical Package for the Social Sciences. It is an effective yet simple software for analyzing data inputs. Common problems when installing SPSS This document contains guidelines to assist in the most common problems with installing SPSS on a Windows personal computer. In most cases, these workaround solutions will work, but if you are still having problems please phone the IT Service Desk on 0116 252 2253 (or email. When writing down the observed values of a categorical variable, you can choose to write the values as words or as numeric codes. Either method of recording categorical variables is valid, but it is often easier to work with numeric codes in SPSS than it is to work with strings. This is because, when referring to the content of a string during a computation, the content must match exactly. If the content of the two strings is not an exact match, the computer will not recognize them as identical. This includes placing an extra space at the end of a string: the human eye won't detect the discrepancy, but the computer will. (Note that if your data was originally recorded in Excel, it is very easy for the values of string variables to accidentally be recorded with extra spaces at the end.) If you have already recorded your categorical variables as strings, you can easily convert them to a numerically coded variable using the Automatic Recode procedure. This procedure assigns each unique category a numeric code, then saves the converted values as a new variable. It also automatically adds value labels: whatever the string value was before becomes the value label. Additionally, if you have used blanks to indicate missing values for string variables, you may have noticed that SPSS doesn't automatically recognize those observations as missing. This is because SPSS, by default, recognizes 'blank' strings as valid values. In this situation, you must use Automatic Recode in order for SPSS to recognize blank strings as missing values. Otherwise, SPSS will consider the 'blank' category as a valid category. To open the Automatic Recode procedure, click Transform > Automatic Recode. A Variable -> New Name: The original variable(s) being transformed, and the name of the new variable(s) that the results will be saved as. B New Name field and Add New Name button: These fields will activate after at least one variable has been added to the Variable -> New Name box. You will need to supply a new variable name and click Add New Name for each variable being recoded. C Recode Starting from: Should the new category numbering be in alphabetical order (Lowest value) or reverse alphabetical order (Highest value) with respect to the original values? This setting is applied to all of the variables being recoded. D Use the same recoding scheme for all variables: When checked, the same numeric code is never re-used across variables, unless the category names are identical. E Treat blank string values as user-missing: When checked, the numeric category assigned to blank strings will be set as a special missing value. This setting must be checked in order for missing values to be properly recognized. To automatically recode variables: • Click Transform > Automatic Recode. • Select the string variable of interest in the left column and move it to the right column. • Enter a new name for the autorecoded variable in the New Name field, then click Add New Name. • SPSS will assign numeric categories in alphabetical order. By default, this means that the lowest numeric categories will be assigned to category names coming first in the alphabet. You can change this so that categories coming later in the alphabet are given the lowest numeric category by clicking Highest value. • If blanks were used to indicate missing values, select the Treat blank string values as user-missing check box. • If you are converting multiple string variables and do not want the same number to be re-used as a category code across multiple variables, select the Use same recoding scheme for all variables check box. • Click OK to finish. Problem Statement In the sample data file, the variable State is a string variable representing whether the student is an in-state student or an out-of-state student. If you create a frequency table of this variable ( Analyze > Descriptive Statistics > Frequencies), you will notice something strange: The dataset has 435 observations in all, and SPSS reports that there are zero missing values. But there is an apparently unlabeled category listed under the 'Valid' categories in the frequency table that has 27 observations. This is because SPSS does not automatically recognize blanks as missing values. (Note: this behavior is different than SAS, which automatically recognizes blanks as missing values for string variables.) In order for our analyses to be accurate, we'll need to fix this issue. Running the Procedure Using the Automatic Recode Dialog Window • Click Transform > Automatic Recode. • Double-click variable State in the left column to move it to the Variable -> New Name box. • Enter a name for the new, recoded variable in the New Name field, then click Add New Name. • Check the box for Treat blank string values as user-missing. • Click OK to finish. Ibm Spss Support Phone Number![]() Using Syntax AUTORECODE VARIABLES=State /INTO state_code /BLANK=MISSING /PRINT. Output Running the procedure will produce the following message in the Output Viewer window: State into state_code (State Residency) Old Value New Value Value Label In state 1 In state Out of state 2 Out of state M 3M This message tells us the mapping scheme that SPSS generated for the categories: 'In state' became 1, 'Out of state' became 2, and blanks became 3, which was set as a special missing value code. You can confirm In the Variable View window, you can see that in addition to copying the original string values to the category labels, SPSS also defined category 3 as 'missing.' Now when we create a frequency table for the recoded variable, it should reflect the proportion of values that are missing: In the output, the recoded blank values are correctly counted as missing, but show their assigned numeric code in the Value Labels column in the output. You can improve the appearance of the missing value category by simply adding a value label (e.g. 'Missing') for that particular code. If you recorded the missing values for a string variable using some kind of non-blank indicator (for example, 999 or -999) and have already defined that user-missing value in the Variable View window, Automatic Recode will preserve the 'missing' designation, but will still convert the category code to be in the range of the other categories. Suppose that the below syntax was applied to a string variable with the valid categories 'blue', 'green', and 'red', with missing values recorded using the code '999'. AUTORECODE VARIABLES=VAR00001 /INTO v1 /GROUP /BLANK=MISSING /PRINT. Excel Support NumberRunning that syntax will produce the following output: User-missing values from VAR00001 Old Value New Value Value Label blue 1 blue green 2 green red 3 red 999 M 4M 999 Here, you can see that observations originally coded as '999' have been recoded to the numeric indicator 4 with the value label '999'. The letter M indicates that the label or code is a missing value indicator. We have not yet discussed the option Use the same recoding scheme for all variables. Ibm Spss Customer Support NumberWhat are some reasons to use this option? • You have many string categorical variables to recode, and do not want to have the same number re-used on unrelated categories.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |