LatentGOLD vs SAS Visual Statistics

LatentGOLD is Windows desktop software for latent class and profile analysis, finite mixture modeling, choice modeling, segmentation, clustering and advanced latent-variable work. Its Basic version includes Cluster, DFactor, Regression and Step3 point-and-click modules. Advanced/Syntax adds complex sampling, multilevel latent class models, continuous latent variables, a point-and-click Markov module and the LG-equations syntax language. Choice options cover first-choice, ranking, best-worst, rating and allocation data. The software includes statistical tests, regression models and scripting, and imports ASCII text and SPSS system files. LatentGOLD 6.1 is listed as compatible with Windows 10 and 11; the maker supports installation only on Windows machines. There is no stated record-count limit, although runtime depends on data, machine speed and requested output. The maker identifies researchers, universities, market researchers, consultants and data analysts as users. Eligible university-affiliated students, researchers and educators can request a free academic single-user license for academic or non-commercial research. Pricing includes a 14-day trial and paid plans; listed standard single-user pricing for Basic + Advanced/Syntax is €795 a year.

SAS Visual Statistics is a statistical visualization and modeling product on SAS Viya. It supports analysis from raw data toward strategic action, with visual model building, variable adjustment, and outlier removal; users can see how those changes affect outcomes. Multiple users can collaborate on the same data model, and the environment supports Python, R, or SAS. Listed techniques include clustering, decision trees, linear and logistic regression, generalized linear and additive models, and nonparametric logistic regression.

Imports include SAS data sets, Excel, delimited text, CSV, DTA, JMP, Parquet, and SPSS. Programmers can access the Viya CAS server through SAS Studio, PROC CAS, Python, R, Lua, Java, and public REST APIs. Native Python Pandas DataFrame integration supports sending DataFrames to CAS and retrieving results for use with packages such as Pandas, matplotlib, Plotly, and Bokeh. SAS Cloud Analytic Services processes data in memory and distributes work across cluster nodes. The product is cloud-deployed, paid, and priced on request; no free plan is listed, but a free trial is available.