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  "Package": "psm3mkv",
  "Title": "Evaluate Partitioned Survival and State Transition Models",
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  "Description": "Fits and evaluates three-state partitioned survival\nanalyses (PartSAs) and Markov models (clock forward or clock\nreset) to progression and overall survival data typically\ncollected in oncology clinical trials. These model structures\nare typically considered in cost-effectiveness modeling in\nadvanced/metastatic cancer indications. Muston (2024).\n\"Informing structural assumptions for three state oncology\ncost-effectiveness models through model efficiency and fit\".\nApplied Health Economics and Health Policy.",
  "License": "GPL (>= 3)",
  "URL": "https://merck.github.io/psm3mkv/, https://github.com/Merck/psm3mkv",
  "BugReports": "https://github.com/Merck/psm3mkv/issues",
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  "Repository": "https://merck.r-universe.dev",
  "Date/Publication": "2024-06-07 19:35:11 UTC",
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  "Maintainer": "Dominic Muston <dominic.muston@merck.com>",
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    "calc_haz_psm",
    "calc_likes",
    "calc_rmd",
    "calc_surv_psmpps",
    "check_consistent_pfs",
    "compare_psm_likes",
    "constrain_survprob",
    "create_dummydata",
    "create_extrafields",
    "find_bestfit",
    "fit_ends_mods_par",
    "fit_ends_mods_spl",
    "graph_psm_hazards",
    "graph_psm_survs",
    "graph_survs",
    "prob_os_psm",
    "prob_os_stm_cf",
    "prob_os_stm_cr",
    "prob_pd_psm",
    "prob_pd_stm_cf",
    "prob_pd_stm_cr",
    "prob_pf_psm",
    "prob_pf_stm",
    "prob_pps_cf",
    "prob_pps_cr",
    "vlookup"
  ],
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      "page": "calc_allrmds",
      "title": "Calculate restricted mean durations for each health state and all three models",
      "topics": [
        "calc_allrmds"
      ]
    },
    {
      "page": "calc_haz_psm",
      "title": "Derive pre and post-progression hazards of death under PSM",
      "topics": [
        "calc_haz_psm"
      ]
    },
    {
      "page": "calc_likes",
      "title": "Calculate likelihoods for three three-state model structures",
      "topics": [
        "calc_likes"
      ]
    },
    {
      "page": "calc_rmd",
      "title": "Calculate restricted mean durations",
      "topics": [
        "calc_rmd"
      ]
    },
    {
      "page": "calc_surv_psmpps",
      "title": "Derive PPS survival function under a PSM",
      "topics": [
        "calc_surv_psmpps"
      ]
    },
    {
      "page": "check_consistent_pfs",
      "title": "Check consistency of PFS definition Check that PFS is defined consistently with TTP and OS in a dataset. This convenience function compares 'pfs.durn' with the lower of 'ttp.durn' and 'os.durn', and checks that the event field 'pfs.flag' is consistent with 'ttp.flag' and 'os.flag' (is 1 when either 'ttp.flag' or 'os.flag' is one).",
      "topics": [
        "check_consistent_pfs"
      ]
    },
    {
      "page": "compare_psm_likes",
      "title": "Compare likelihoods of PSMs",
      "topics": [
        "compare_psm_likes"
      ]
    },
    {
      "page": "constrain_survprob",
      "title": "Constrain survival probabilities according to hazards in a lifetable Recalculated constrained survival probabilities (by week) as the lower of the original unadjusted survival probability and the survival implied by the given lifetable (assumed indexed as years).",
      "topics": [
        "constrain_survprob"
      ]
    },
    {
      "page": "create_dummydata",
      "title": "Create dummy dataset for illustration",
      "topics": [
        "create_dummydata"
      ]
    },
    {
      "page": "create_extrafields",
      "title": "Create the additional time-to-event endpoints, adjusting for cutpoint",
      "topics": [
        "create_extrafields"
      ]
    },
    {
      "page": "find_bestfit",
      "title": "Find the \"best\" survival regression from a list of model fits",
      "topics": [
        "find_bestfit"
      ]
    },
    {
      "page": "fit_ends_mods_par",
      "title": "Fit multiple parametric survival regressions to the multiple required endpoints",
      "topics": [
        "fit_ends_mods_par"
      ]
    },
    {
      "page": "fit_ends_mods_spl",
      "title": "Fit multiple spline regressions to the multiple required endpoints",
      "topics": [
        "fit_ends_mods_spl"
      ]
    },
    {
      "page": "graph_psm_hazards",
      "title": "Graph the PSM hazard functions",
      "topics": [
        "graph_psm_hazards"
      ]
    },
    {
      "page": "graph_psm_survs",
      "title": "Graph the PSM survival functions",
      "topics": [
        "graph_psm_survs"
      ]
    },
    {
      "page": "graph_survs",
      "title": "Graph the observed and fitted state membership probabilities",
      "topics": [
        "graph_survs"
      ]
    },
    {
      "page": "prob_os_psm",
      "title": "Calculate probability of being alive in a partitioned survival model",
      "topics": [
        "prob_os_psm"
      ]
    },
    {
      "page": "prob_os_stm_cf",
      "title": "Calculate probability of being alive under the state transition clock forward model",
      "topics": [
        "prob_os_stm_cf"
      ]
    },
    {
      "page": "prob_os_stm_cr",
      "title": "Calculate probability of being alive under the state transition clock reset model",
      "topics": [
        "prob_os_stm_cr"
      ]
    },
    {
      "page": "prob_pd_psm",
      "title": "Calculate membership probability of progressed disease state in a partitioned survival model",
      "topics": [
        "prob_pd_psm"
      ]
    },
    {
      "page": "prob_pd_stm_cf",
      "title": "Calculate probability of having progressed disease under the state transition clock forward model",
      "topics": [
        "prob_pd_stm_cf"
      ]
    },
    {
      "page": "prob_pd_stm_cr",
      "title": "Calculate probability of having progressed disease under the state transition clock reset model",
      "topics": [
        "prob_pd_stm_cr"
      ]
    },
    {
      "page": "prob_pf_psm",
      "title": "Calculate probability of being progression free in partitioned survival model",
      "topics": [
        "prob_pf_psm"
      ]
    },
    {
      "page": "prob_pf_stm",
      "title": "Calculate probability of being progression free in either state transition model (clock forward or clock reset)",
      "topics": [
        "prob_pf_stm"
      ]
    },
    {
      "page": "prob_pps_cf",
      "title": "Calculate probability of post progression survival under the state transition clock forward model",
      "topics": [
        "prob_pps_cf"
      ]
    },
    {
      "page": "prob_pps_cr",
      "title": "Calculate probability of post progression survival under the state transition clock reset model",
      "topics": [
        "prob_pps_cr"
      ]
    },
    {
      "page": "vlookup",
      "title": "VLOOKUP function",
      "topics": [
        "vlookup"
      ]
    }
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      "headings": [
        "Introduction",
        "Obtaining a suitable dataset",
        "Fit survival curves to the relevant endpoints",
        "Parametric distributions",
        "Royston-Parmar splines models",
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      "check": "OK",
      "buildurl": "https://github.com/r-universe/merck/actions/runs/26948137402"
    }
  ]
}