Tag Archives: survey monkey data analysis

Dedoose Mixed Methods And Qualitative Research Software Version 2.5

Although we have been posting these details on the forum, it’s been a while since we updated the blog.  We’ve made some major structural changes to Dedoose on the backend that has once again boosted performance dramatically.   Large projects are seeing a massive increase is load times,  our main large test project loads in about 9 seconds now instead of ~45!     Additionally we’ve been getting a lot of request from QSR International’s NVivo users to be able to use their data inside Dedoose.   Many NVivo users have asked us if migration is possible and our crack team has found a solution and built an NVivo export strategy that can export your entire project’s data into a giant excel spreadsheet with the codes or nodes applied to every segment, and, upon import to Dedoose, re-links these coded excerpts to their source document.   As part of the overall mission, we built two different Dedoose project importers, one that can handle a spreadsheet and documents like the NVivo example and one that can handle a spreadsheet like what most survey tools output (all inspired by research using SurveyMonkey).  This being said, it’s now possible to get your data into Dedoose from just about any source including NVivo, MaxQDA, Atlas.ti, Survey Monkey, and just about anything else you can generate a spreadsheet from.  If your project includes both qualitative and quantitative data, like some research with SurveyMonkey with both scale and open-ended questions, the importer will do something amazing work.   Upon import, the importer analyzes all values to determine which columns are numbers, dates, true/false, multiple choice, etc.  It then creates the proper descriptor fields for this data, create the descriptors, creates a transcript for every record with question/answer for each qualitative data column in the output, creates a tag/code for that question, creates an excerpt for each question/answer in each transcript, applies the tag for that question, and also links the appropriate quantitative information (descriptor).    In one fell swoop it complete’s what we refer as the indexing phase of a study, all you need to do now is create additional qualitative codes/tags, apply them to the existing excerpts and begin your analysis….or just start your analysis immediately using your descriptor data and indexed qualitative responses!

These imports need to be processed by our engineering team, so if you are interested please email [email protected] and we will be happy to assist.

At the same time, we’ve had our team members working on improving other aspects of Dedoose, and will be releasing a slew of updates shortly.  One of the more interesting aspects are a complete re-write of the charting system.   As we have optimized so many aspects of Dedoose, it appears that the remaining major draw on system resources are attributable to the interactive charts.   After our team has re-built them for performance we are once again seeing incredible performance increases, for example the slowest chart: Tag Co-Occurrence on one large data set takes about 2-3 minutes to fully render all cells, compare that to about 6 seconds in our new optimized versions for a full 30x speed increase.  In addition these new charts use a fraction of the memory, and offer customization that was not possible in our previous generation, such as the selection of different coloring routines.

As usual our team has been cranking out tons of bug fixes, performance enhancements, feature improvements, and requested features.  Stay tuned here, or check out the forum to keep up-to-date, keep an eye out for a slew of new video tutorials, and, coming very soon, a brand new look for our website.

Happy Coding!