Good transition software for dealing with mixed-methods data for first timers
May 01, 2018
Good transition software for dealing with mixed-methods data for first timers
Score 7 out of 10
Vetted Review
Verified User
Modules Used
- IBM SPSS Statistics
Overall Satisfaction with IBM SPSS
I use SPSS to combined datasets, easily modify individual cases, input quantitative data, collect/ modify qualitative data, and conduct quick parametric and non-parametric analyses.
- Imputing mixed-methods data
- Quick user-friendly analyses
- Non-parametric statistics
- Limited coding capacity for modifying the analysis
- Need to manually add in code for follow-up analyses
- Not easy to modify and track database management
- Only prints up to 2 decimals in the output
SPSS has made it very easy to convert our datasets into multiple types of formats like SAS. In addition, it reads multiple types of formats like Excel and SAS.
We use it to track data collection to provide process evaluation data for intervention programs.
JMP is user-friendly like SPSS but is more limited in terms of data analyses.
SAS is better for managing and modifying large datasets. SAS also provides more customization for analyzing things like group differences. However, SAS does not handle modifying string responses well. It also requires a learning curve. Finally, its hard to past SAS output into a well readable format.
SAS is better for managing and modifying large datasets. SAS also provides more customization for analyzing things like group differences. However, SAS does not handle modifying string responses well. It also requires a learning curve. Finally, its hard to past SAS output into a well readable format.