G2

Alan Antonio R.

Assistent Professor

Small-Business (50 or fewer emp.)

8/3/2026

"Design of Metal Organic Frameworks Using SAT/STATA"

4.5/5

What do you like best about SAS/STAT?

I have access to a broad set of procedures—for example, PROC MIXED, PROC GLM, PROC LOGISTIC, PROC PHREG, and others—that cover an enormous range of statistical models (linear, mixed-effects, survival, and categorical), with mature, well-tested implementations. For complex study designs such as unbalanced data, repeated measures, and multilevel models, the mixed-model procedures in particular are widely considered a strong option. Review collected by and hosted on G2.com.

What do you dislike about SAS/STAT?

The cost, licensing is expensive (often five or six figures annually for enterprise seats), and it's typically negotiated per-institution rather than transparently priced. For smaller labs, startups, or individual researchers, that's a real barrier compared to R or Python being free. Review collected by and hosted on G2.com.

What problems is SAS/STAT solving and how is that benefiting you?

Computational MOF screening (for example, using databases such as CoRE MOF or hypothetical MOF libraries) can produce thousands to millions of candidate structures, each characterized by properties like surface area, pore volume, and gas uptake. Regression and ANOVA methods can then be used to pinpoint which structural descriptors—such as pore size, metal node type, and linker chemistry—are truly driving performance. This helps separate real signal from noise when exploring such large, high-dimensional parameter spaces. Review collected by and hosted on G2.com.