The following questions have already been submitted. If you have another question, you can mail them to firstname.lastname@example.org.
- What are the possibilities for multilevel analysis in the three software packages?
- I'm mostly interested in using the R graphics, and how to combine them with SPSS.
- Overview basic statistical methods ANOVA, FET, for beginner.
- These packages have research areas they perform well in. Can you please specify the areas that your package can perform well in and thier relative compatibility?
- SPSS seems to be not very useful when in need to produce repeated measures statistics with scaled classes. Is this true? Should I always have to use SAS for this?
- A number of surrogate models are built with different number of data samples. I would like to find a correlation between the number of samples and the root-relative-square-error of each model. This could be done by finding an empirical law (linear, polynomial, ... ) which can fit the data (error versus the number of samples). How can I do this?
- When and how to calculate ES (effect sizes)?
- How to deal with missing data? (how to put a 'rule' into the calculation -syntax- of a total score, not to calculate a total score when 3 or more data are missing?)
- How to integrate two variables into one?
- How to interprete (read: how to translate into narrative text) Odds ratios?
- How (and comments on) to calculate inter-rater reliablity with several (75) raters and few (6) cases?
- Supposedly, there is now a better link between JMP and SAS. I thought the idea was that SAS could now be called using the JMP interface? How does this work? How user-friendly is this?