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...It guides users through the full workflow across three tabs: Model setup (formula input with live parsing, CSV data upload with auto-detected variable types, effect size sliders, and correlation editing), Analysis configuration (find power for a given sample size or find the minimum sample size for a target power, with multiple testing correction and scenario analysis), and Results (interactive charts, exportable tables, and auto-generated Python replication scripts). Supports both standard linear models and mixed-effects models. Additional features include analysis history, configurable scenarios, and built-in documentation.

...Designed for researchers, PhD scholars, professors, and analysts, it provides visual model building, measurement assessment, structural model analysis, and reproducible research workflows without subscriptions or cloud dependency. Features include: • PLS-SEM & CB-SEM • Bootstrapping, mediation, moderation & conditional process analysis • HTMT, AVE, Composite Reliability, Cronbach's Alpha, Fornell-Larcker • VIF, f² effect size, indirect effects, Q² blindfolding, PLSpredict, CVPAT • Multi-Group Analysis (MGA), HOC, MICOM • IPMA, NCA, nonlinear effects, FIMIX-PLS, PLS-POS, endogeneity checks • EFA, CVI, measurement validation, fsQCA • APA report generation and R/Python/Lavaan export Fully offline and available for Windows, macOS, and Linux. ...

...The program is multi-grid (finite differences or finite elements), multi-algebra (plug-in analysis kernels), multi-model (simple standardized interface). The program supports reduced-order data assimilation methods, as well as Ensemble assimilation approaches such as the Ensemble Kalman Filter. Recent additions include extensions towards simultaneous assimilation and downscaling (AMICO project), and a toolbox for ensemble assessment (SCRUM project).

The new version of MinimPy (MinimPy2) is available for download at: https://osdn.net/dl/minimpy2/MinimPy2.zip Please send your feedback about this new version to mahmood.saghaei@gmail.com (include MinimPy2 in the subject) ============================================================ MinimPy is a desktop application program for sequential allocation of subjects to treatment groups in clinical trials by using the method of minimization. Comprehensive reference help is available at http://minimpy.sourceforge.net MinimPy has been fully described in the following article: Saghaei, M. and Saghaei, S. (2011) Implementation of an open-source customizable minimization program for allocation of patients to parallel groups in clinical trials. ...

...Features: - Capable of high order factorial designs (> 2 factors) - Within and mixed analyses of variance provide corrections for violations of sphericity (Huynh-Feldt, Greenhouse-Geisser, Box) - A variety of data transformations can be applied (log10, reciprocal, arcsine, square-root, and Windsor) - Generalized eta-squared measures of effect size - Post-hoc power analysis (should match G*Power) - Outputs include tables of estimated marginal means - Up to 4-way interaction plots with errorbars (png, svg) - Confidence intervals account for within-subject variability (where applicable; Loftus and Masson, 1994) - Non-proprietary HTML output files - Non-proprietary codebase Gotchas: - Assumes balanced designs