SAS® for Mixed Models, 2nd edition Edited by Littell, R. C., Milliken, G. A., Stroup, W. W., Wolfinger, R. D., and Schabenberger, O.

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Conventional and glyphosate-resistant maize yields across plant densities in single- and twin-row configurations (2011, methodology): “Weed biomass, LAI, and grain yield were analyzed based on a general linear mixed model procedure using SAS software, [release 9.2, SAS Institute Inc., Cary, NC; (Littell et al., 2006)] within each location, with data and discussion presented by location.”
Antibiosis, mycoparasitism, and colonization success for endophytic Trichoderma isolates with biological control potential in Theobroma cacao (2008, methodology): “Heterogeneous within-isolate variances were modeled using the GROUP = option (Littell et al., 2006) of the REPEATED statement in SAS/ STAT Proc MIXED (SAS Institute Inc.”
How do Data Science Workers Collaborate? Roles, Workflows, and Tools (2020, methodology): “Various tools have also been built for supporting data science work, including programming languages such as Python or R, or statistical analysis tools such as SAS [58] and SPSS [63], an integrated developing environment (IDE) Jupyter Notebook [31, 52], and automated model building systems such as A”