Archive for August, 2006
We received a question from Ilan Shrira, who got an error while saving a file:
I just bought a 120 gigabyte external hard drive, and whenever I try to save an SPSS file
that’s more than 4 gigabyte onto it, it stops and says “Warning #5322, The attempt to save the data file has failed because the disk is full, an I/O error has occurred, the variable dictionary is invalid, or the task was interrupted”
I didn’t have any trouble saving 2 or 3 gigabyte files of the save type. Is is possible that there’s some other kind of glitch in my file.”
To our information there is no limitation in file size, variables or cases. This information is not checked with SPSS, since we do not have a support contract. If anyone else has and is willing to ask SPSS about this, we would be very thankfull. But, the cause isÂ probably an error in the data or variables.
TheÂ error has been discussed in the SPSSX-L mailinglist. In this discussion Raynald Levesque suggests the following cause to the problem:
“If you have string variables, check that the number of characters differs
from the declared length of that variable.
eg if you have a variable declared as format A2 but that variable contains 3
characters. In recent versions of SPSS, more integrity tests are performed
when saving a file and this would cause an error.”
You can check your file by hand or use the automated method Raynald suggest in his second post.
August 23rd, 2006
We get a lot of questions about regression analysis. We have dug into this and decided to write a post about it, so we can help everyone with this.
You do a regression when you assume that a variable is influencing another one, like in the following example: We assume that cars that run on Diesel have higher costs.
To test this assumption, we run a Linear Regression in SPSS. Take the following steps:
- Define your dependent and independent variable. In our example Fuel is the indepent variable and Costs is the dependent one.
- Click Analyze
- Go to Regression and click Linear
- Click “Fuel” into the Independent variable field, and “Costs” into the Dependent variable field.
The output exists of:
1 Model Summary, in which you can find the relation between the variables.
R stands for the correlation and gives us the relation between the dependent and the independent variables. The correlation between Fuel and Costs is ,839.
R Square is the proportion of variance in the dependent variable (Costs) which can be predicted from the independent variable (Fuel). This value indicates that 70% of the variance in costs can be predicted from the variable fuel. The Adjusted R-square tries to give an even better calculation for the whole population.
2 ANOVA, which holds data about the significance of the regressionmodel.
The value under Sig. holds the significance value of the regression. In most cases this should be under 0.05. In our example this is 0.00, better it cannot get!
3 Coefficients, gives information about the first line of regression.
Conclusion would be that this regression analysis is significant and that 70% of the variance in costs can be predicted from the variable fuel.
Please find below the SPSS file we used to create this example. Just one note, the information in the SPSS file is not based on anything. Even more, it’s just random data. Please don’t sue us.
Linear Regression Example Cars
August 21st, 2006
August 17th, 2006
This week we got a question from Timo.
Is it possible to use syntax when recoding variables? For example, if I
had a variable that included the following values:
and I wanted to recode any values that included ‘bird’ into a new value
‘bird’, can I do this with the Recode transformation?
To solve to problem the following syntax is an option:
DATA LIST LIST /var1(A15).
DO IF INDEX(UPCASE(var1),”BIRD”) > 0 .
- COMPUTE newVar=”BIRD”.
Do you also need an answer to your SPSS question, submit your question here.
August 17th, 2006
If you are curious about the latest developments in SPSS, and want to check out the new – still to become available in store – version of SPSS (15.0), visit this page about the See it in SPSS: free seminar exclusively for SPSS customers. Unfortunately for us, only in the US.
August 15th, 2006