Re: When to use PSPP and not SPSS?

[John Darrington]

Hello Doug,

Thank you very much for making us aware of these issues.  Some of them are,
like you say, easily fixable.  Others, are not so easy.

If you would be willing to spend the time working with the developers to 
solve these issues, please subscribe to the pspp developers list at
https://lists.gnu.org/mailman/listinfo/pspp-dev


Regards,

John

On Tue, Jan 07, 2014 at 10:53:39PM -0800, Douglas Bonett wrote:
     I was asked to evaluate PSPP as a possible substitute for SPSS for all of
     our undergraduate social science statistics courses. The latest version of
     PSPP is a great improvement over previous versions. Here is a list of some
     easily fixable bugs/issues when operating in GUI mode:
     
     
     When entering k columns of data one column at a time, an error message
     occurs when entering a value in the second row of column 2, 3, ..., k.
     
     
     ?pair 0? is printed instead of ?pair 1? in the paired-samples t-test
     
     
     Certain selected measures of association are ignored in Crosstabs.
     
     
     Change ?Significance? to ?Sig.? in linear regression and one-way ANOVA
     output to be consistent with SPSS and other PSPP analyses.
     
     
     Only integer percentage confidence levels are allowed. Non-integer values
     (e.g. 97.5%) are needed for Bonferroni adjustments (like SPSS).
     
     
     Information in all analysis-specification screens is lost when returning to
     those screens (as if Reset had been selected).
     
     
     Confidence intervals are needed in the linear regression output (like 
SPSS).
     
     
     A vertical line is needed after the DV variable name in the output of the
     independent t-test (see output of the linear contrast table in one-way
     ANOVA as a guide)
     
     
     The following easily-programmed features are not in SPSS but are very
     important and would make PSPP more useful than SPSS for classroom use now
     that APA is requiring confidence intervals in all of its journals:
     
     
     Confidence intervals for linear contrasts in one-way ANOVA
     
     
     Confidence intervals for Pearson correlations
     
     
     Confidence intervals for measures of association in Crosstabs for those
     measures where standard errors are computed.
     
     
     
     Doug
     
     Director, Center for Statistical Analysis in the Social Science
     
     University of California, Santa Cruz
     
     
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