Since my Ph.D. dissertation constitutes an empirical investigation, quantitative data analysis is an essential part of the corresponding research study. In order to perform quantitative data analysis in a reproducible fashion, I decided to design and develop custom software for both data collection and data analysis. For that purpose, I have chosen to use R statistical programming language and environment, which is rather natural, considering that open source software, such as R, is the core topic of my research, not to mention additional bonuses of great flexibility and ability to make my research as reproducible as possible. I had to learn and master R as well as many other wonderful open source software packages, which all comprise a large part of enormous and breathtaking R ecosystem, along with its mostly friendly and helpful community.

edaProjectLicense

edaProjectAgeMixture

cfaModel

In the spirit of open source and open science, I have released my dissertation research software, called DISS-FLOSS, under open source (MIT) license and published it on GitHub portal (please see this GitHub repository). I have some plans to further improve DISS-FLOSS, as noted in my Research Agenda.

If you use DISS-FLOSS or its parts in your research or any other projects, please attribute it accordingly by citing as follows:

Blekh, A. L. (2014). Research software for quantitative analysis of open source software ecosystem using structural equation modeling. Version 1.0.2. [Software] Retrieved from http://github.com/abnova/diss-floss-official. doi:10.5281/zenodo.13143