Analysis of Rare Disease Datasets Using Advanced Sas Techniques Survival Analysis, Mixed Models and Machine Learning Algorithms
Abstract: The use of techniques in SAS for analysis showcases the advancement of data analysis methods in scientific studies. It is essential to employ data visualization methods, like R shiny apps to make sense of intricate data sets especially when dealing with rare diseases and new endpoints. Analyzing data from diseases presents challenges such as small sample sizes and the requirement for fresh endpoints, which call for creative strategies in visualizing and analyzing data. Leveraging analysis with SAS MCMC procedure provides a framework to tackle the complexities of rare disease data leading to more precise statistical conclusions. By combining techniques with innovative data visualization methods researchers can gain valuable insights from rare disease data ultimately improving research outcomes and patient care.
Keywords: SAS, data visualization, rare diseases, statistical analysis, R shiny apps
How to Cite?: Arvind Uttiramerur, "Analysis of Rare Disease Datasets Using Advanced Sas Techniques Survival Analysis, Mixed Models and Machine Learning Algorithms", Volume 11 Issue 3, March 2022, International Journal of Science and Research (IJSR), Pages: 1594-1596, https://www.ijsr.net/getabstract.php?paperid=SR24430155112, DOI: https://dx.doi.org/10.21275/SR24430155112