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  "Package": "PHInfiniteEstimates",
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  "Title": "Tools for Inference in the Presence of a Monotone Likelihood",
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  "Date": "2023-11-23",
  "Author": "John E. Kolassa and Juan Zhang",
  "Maintainer": "John E. Kolassa <kolassa@stat.rutgers.edu>",
  "Description": "Proportional hazards estimation in the presence of a\npartially monotone likelihood has difficulties, in that finite\nestimators do not exist.  These difficulties are related to\nthose arising from logistic and multinomial regression.\nReferences for methods are given in the separate function\ndocuments.  Supported by grant NSF DMS 1712839.",
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      "date": "2020-02-17"
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      "date": "2020-03-09"
    },
    {
      "version": "1.2",
      "date": "2020-03-25"
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    {
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      "date": "2020-03-29"
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    "andersenplot",
    "arjasplot",
    "bestbeta",
    "checkcensor",
    "checkresults",
    "compareplot",
    "compete.simulation",
    "convertbaselineltolr",
    "convertmtol",
    "convertstoml",
    "drawdiagram",
    "fixcoxph",
    "gehan.wilcoxon.test",
    "heinzeschemper",
    "inference",
    "lrapproximations",
    "network",
    "newllk",
    "pllk",
    "reduceLR",
    "simcode",
    "simultaneouscoverage",
    "summarizefits",
    "summarizetable",
    "survregpredict",
    "testcox"
  ],
  "_datasets": [
    {
      "name": "voter.ml",
      "title": "Subset of British elections data used in (Kolassa 2016).  Data are from (Sanders et al. 2007).",
      "object": "voter.ml",
      "file": "voter.ml.RData",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Labor",
        "Liberal.Democrat",
        "education",
        "voter",
        "party",
        "chid",
        "alt"
      ],
      "rows": 201,
      "table": true,
      "tojson": true
    }
  ],
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    {
      "page": "aalenjohansen",
      "title": "Calculate the Aalen-Johansen (1978) estimate in the Competing risk context.  See Aalen, Odd O., and Søren Johansen. \"An Empirical Transition Matrix for Non-Homogeneous Markov Chains Based on Censored Observations.\" Scandinavian Journal of Statistics 5, no. 3 (1978): 141-50. Accessed January 15, 2021. http://www.jstor.org/stable/4615704.",
      "topics": [
        "aalenjohansen"
      ]
    },
    {
      "page": "andersenplot",
      "title": "Plot hazards for two strata for each time.  At times with an event in one but not the other group, the fitted hazard remains constant, and so the plot is a step function.  If hazards are proportional between strata, then the plot should be close to a straight line.",
      "topics": [
        "andersenplot"
      ]
    },
    {
      "page": "arjasplot",
      "title": "Examine the potential role of treatment in treatment in a model already including sex. Straight lines that are not 45 degrees indicate the appropriateness of new variable as a linear effect.",
      "topics": [
        "arjasplot"
      ]
    },
    {
      "page": "bestbeta",
      "title": "Newton Raphson Fitter for partial likelihood",
      "topics": [
        "bestbeta"
      ]
    },
    {
      "page": "checkcensor",
      "title": "Check how censoring impacts sampling properties of KM fit and log rank test.",
      "topics": [
        "checkcensor"
      ]
    },
    {
      "page": "checkresults",
      "title": "Produce a graphical assessment of Monte Carlo experiment on fidelity of proportional hazards regression to the uniform ideal.",
      "topics": [
        "checkresults"
      ]
    },
    {
      "page": "compareplot",
      "title": "Plot resuts of simcode",
      "topics": [
        "compareplot"
      ]
    },
    {
      "page": "compete.simulation",
      "title": "Simulate from a competing risk model with correlated log normal errors, and plot various estimates.",
      "topics": [
        "compete.simulation"
      ]
    },
    {
      "page": "convertbaselineltolr",
      "title": "Convert a baseline logit model data set, formatted in the long form as described in the documentation for mlogit.data from mlogit package, to a conditional logistic regression.",
      "topics": [
        "convertbaselineltolr"
      ]
    },
    {
      "page": "convertmtol",
      "title": "Convert a polytomous regression to a conditional logistic regression.",
      "topics": [
        "convertmtol"
      ]
    },
    {
      "page": "convertstoml",
      "title": "Convert a proportional hazards regression to a multinomial regression.",
      "topics": [
        "convertstoml"
      ]
    },
    {
      "page": "drawdiagram",
      "title": "Draw diagram for toy PH example.",
      "topics": [
        "drawdiagram"
      ]
    },
    {
      "page": "fixcoxph",
      "title": "Remove observations from a proportional hazards regression, and return the fit of the reduced model.",
      "topics": [
        "fixcoxph"
      ]
    },
    {
      "page": "gehan.wilcoxon.test",
      "title": "Perform Gehan's application to the Wilcoxon test for multiple samples, testing for equivalance of survival curve.  See Klein and Moeschberger (1997) Survival Analysis (7.3.3) and pp. 193-194.",
      "topics": [
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      ]
    },
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      "title": "Simulate operating characteristics of repaired Cox regression and competitors.",
      "topics": [
        "heinzeschemper"
      ]
    },
    {
      "page": "inference",
      "title": "Perform inference on conditional sample space.",
      "topics": [
        "inference"
      ]
    },
    {
      "page": "lrapproximations",
      "title": "Assess the accuracy of the log rank statistic approximation to the true value, in the case without censoring.  Provides plots of statistics, and empirical test level.",
      "topics": [
        "lrapproximations"
      ]
    },
    {
      "page": "network",
      "title": "This function enumerates conditional sample spaces associated with logistic regression,",
      "topics": [
        "network"
      ]
    },
    {
      "page": "newllk",
      "title": "Proportional hazards partial likelihood, using Breslow method for ties, excluding some observations.",
      "topics": [
        "newllk"
      ]
    },
    {
      "page": "PHInfiniteEstimates",
      "title": "PHInfiniteEstimates: Tools for Proportional Hazards Estimation, and Inference on the Associate Parameters, when Other Parameters are Estimated at Infinity.",
      "topics": [
        "PHInfiniteEstimates"
      ]
    },
    {
      "page": "pllk",
      "title": "Partial likelihood for proportional hazards",
      "topics": [
        "pllk"
      ]
    },
    {
      "page": "reduceLR",
      "title": "Reduce a logistic regression with monotone likelihood to a conditional regression with double descending likelihood.",
      "topics": [
        "reduceLR"
      ]
    },
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      "title": "Simulate Weibull survival data from a model, perform reduction to remove infinite estimates, and calculate p values.",
      "topics": [
        "simcode"
      ]
    },
    {
      "page": "simultaneouscoverage",
      "title": "Calculate simultaneous coverage of pointwise confidence intervals.",
      "topics": [
        "simultaneouscoverage"
      ]
    },
    {
      "page": "summarizefits",
      "title": "Summarize proportional hazards fits",
      "topics": [
        "summarizefits"
      ]
    },
    {
      "page": "summarizetable",
      "title": "Summarize the results of simulations investigating operating conditions for the data reduction method to avoid monotone likelihood.  Files are of form \"hsxxx\", for xxx numerals.",
      "topics": [
        "summarizetable"
      ]
    },
    {
      "page": "survregpredict",
      "title": "Fit survival probabilties from a survreg object.",
      "topics": [
        "survregpredict"
      ]
    },
    {
      "page": "testcox",
      "title": "Test size of asymptotic Cox tests.",
      "topics": [
        "testcox"
      ]
    },
    {
      "page": "voter.ml",
      "title": "Subset of British elections data used in (Kolassa 2016).  Data are from (Sanders et al. 2007).",
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    }
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