{ "_id": "6a16b35cacfb0bcc41d854cf", "Package": "jmSurface", "Title": "Semi-Parametric Association Surfaces for Joint\nLongitudinal-Survival Models", "Version": "0.1.0", "Authors@R": "person(\"Atanu\", \"Bhattacharjee\", \nemail = \"atanustat@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-5757-5513\"))", "Description": "Implements interpretable multi-biomarker fusion in joint\nlongitudinal-survival models via semi-parametric association\nsurfaces. Provides a two-stage estimation framework where Stage\n1 fits mixed-effects longitudinal models and extracts Best\nLinear Unbiased Predictors ('BLUP's), and Stage 2 fits\ntransition-specific penalized Cox models with tensor-product\nspline surfaces linking latent biomarker summaries to\ntransition hazards. Supports multi-state disease processes with\ntransition-specific surfaces, Restricted Maximum Likelihood\n('REML') smoothing parameter selection, effective degrees of\nfreedom ('EDF') diagnostics, dynamic prediction of transition\nprobabilities, and three interpretability visualizations\n(surface plots, contour heatmaps, marginal effect slices).\nMethods are described in Bhattacharjee (2025, under review).", "License": "GPL (>= 3)", "Encoding": "UTF-8", "RoxygenNote": "7.3.3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-27 08:59:31 UTC", "User": "root" }, "Author": "Atanu Bhattacharjee [aut, cre] (ORCID:\n)", "Maintainer": "Atanu Bhattacharjee ", "Repository": "https://atanubhattacharjee.r-universe.dev", "Date/Publication": "2026-02-25 10:20:02 UTC", "RemoteUrl": "https://github.com/cran/jmSurface", "RemoteRef": "HEAD", "RemoteSha": "8ca3b43ec6504fe1e9e0e6075f1779056d2cd5fd", "MD5sum": "7bf7d369d8fa4268c2b9d0954d2ba69f", "_user": "atanubhattacharjee", "_type": "src", 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