Statistical Analysis
Apps v3.4
MindStat
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Statistical Analysis
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R Engine — Click to Load
MindStat Statistical Analysis
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Wide ↔ Long
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0.3
0.30
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30%

ℹ️ Note: Loadings are computed via first-eigenvector decomposition (EFA-style approximation) — not iterative ML with gradient/Hessian. WLSMV not implemented — for ordinal indicators use R lavaan. Fit indices (CFI/TLI/RMSEA/SRMR) are correctly computed from implied covariance.
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RBF Neural Network — Time Series Forecasting
Radial Basis Function network with k-means++ centres for non-linear forecasting
Bayesian Neural Network — MC Dropout
MC Dropout for Bayesian uncertainty estimation

One-way MANOVA with Box's M, Mardia, Levene assumption checks · four multivariate F-approximations · multivariate partial η² for every statistic · Bonferroni univariate follow-up.
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