SurvivalProcessingPipeline: Survival data procesing

In terminological/uk-covid-datatools: Functions for sourcing, cleaning and calculating Rt for uk covid timeseries data

Description

Survival data procesing

Survival data procesing

Super class

ukcovidtools::PassthroughFilesystemCache -> SurvivalProcessingPipeline

Methods

Public methods

• SurvivalProcessingPipeline$new()

• SurvivalProcessingPipeline$generateSurvivalData()

• SurvivalProcessingPipeline$generateNoAgeSurvivalData()

• SurvivalProcessingPipeline$getMaxDate()

• SurvivalProcessingPipeline$transitionMatrix()

• SurvivalProcessingPipeline$generateMultistateSurvivalData()

• SurvivalProcessingPipeline$createSurvivalSurfaces()

• SurvivalProcessingPipeline$plotSurvivalSurface()

• SurvivalProcessingPipeline$plotIncidenceSurface()

• SurvivalProcessingPipeline$plotProbabilityMatrix()

• SurvivalProcessingPipeline$clone()

Inherited methods

• ukcovidtools::PassthroughFilesystemCache$getDaily()

• ukcovidtools::PassthroughFilesystemCache$getHashCached()

• ukcovidtools::PassthroughFilesystemCache$getSaved()

• ukcovidtools::PassthroughFilesystemCache$unloadCache()

---

Method new()

Usage

SurvivalProcessingPipeline$new(providerController, ...)

---

Method generateSurvivalData()

generate survival data and right censored data from

Usage

SurvivalProcessingPipeline$generateSurvivalData(
  df,
  idVar,
  startDateVar,
  endDateExpr,
  statusExpr = if_else(is.na({     {         endDateExpr     } }), 0, 1),
  censoredDateExpr = max({     {         endDateExpr     } }, na.rm = TRUE),
  ageVar = "age",
  ageBreaks = c(-Inf, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80,
    Inf),
  ageLabels = c("0-4", "5-9", "10-14", "15-19", "20-24", "25-29", "30-34", "35-39",
    "40-44", "45-49", "50-54", "55-59", "60-64", "65-69", "70-74", "75-79", "80+"),
  ageReferenceCat = NA_character_,
  statusLabels = c("censored", "died")
)

Arguments

path

- path to the ff100 file

Returns

data set in survival format including status, time, left, right, ageCat columns

---

Method generateNoAgeSurvivalData()

Usage

SurvivalProcessingPipeline$generateNoAgeSurvivalData(
  df,
  idVar,
  startDateVar,
  endDateExpr,
  statusExpr = if_else(is.na({     {         endDateExpr     } }), 0, 1),
  censoredDateExpr = max({     {         endDateExpr     } }, na.rm = TRUE),
  statusLabels = c("censored", "died")
)

---

Method getMaxDate()

Usage

SurvivalProcessingPipeline$getMaxDate(df, dateCols)

---

Method transitionMatrix()

generate transition matrix with enquoted tidy column sepecifications

Usage

SurvivalProcessingPipeline$transitionMatrix(...)

Arguments

...

a set of mappings

Returns

a transistion matrix

---

Method generateMultistateSurvivalData()

generate survival data and right censored data from a multistate model

Usage

SurvivalProcessingPipeline$generateMultistateSurvivalData(
  df,
  idVar,
  transMatrix,
  ageVar = "age",
  censoringDateExpr = getMaxDate(df, dateCols),
  startDateCol = names(allowableTransitions)[1],
  ageBreaks = c(-Inf, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80,
    Inf),
  ageLabels = c("0-4", "5-9", "10-14", "15-19", "20-24", "25-29", "30-34", "35-39",
    "40-44", "45-49", "50-54", "55-59", "60-64", "65-69", "70-74", "75-79", "80+"),
  ageReferenceCat = NA_character_,
  ...
)

Arguments

path

- path to the ff100 file

Returns

data set in survival format including status, time, left, right, ageCat columns

---

Method createSurvivalSurfaces()

for a set of model parameters, calculate the distributions and median

Usage

SurvivalProcessingPipeline$createSurvivalSurfaces(
  modelParameterDf,
  days = 30,
  timepoints = seq(0.1, days, length.out = 100)
)

Arguments

modelParameterDf

- a data frame set of parameters for a range of models as param, value columns

days

- the time frame of the prediction

Returns

an dataframe of ageCat and time varying surfaces, including pdfs, cdfs and medians, with high and low estimates

---

Method plotSurvivalSurface()

plot a survival surface as a CDF

Usage

SurvivalProcessingPipeline$plotSurvivalSurface(surfacesDf, distr)

Arguments

surfacesDf

- an dataframe of ageCat and time varying surfaces, including pdfs, cdfs and medians, with high and low estimates

distr

- a single distribution to plot

Returns

a plot of the survival surface (1-cdf)

---

Method plotIncidenceSurface()

plot a survival surface as a PDF

Usage

SurvivalProcessingPipeline$plotIncidenceSurface(surfacesDf, distr)

Arguments

surfacesDf

- an dataframe of ageCat and time varying surfaces, including pdfs, cdfs and medians, with high and low estimates

distr

- a single distribution to plot

Returns

a plot of the survival surface as pdf

---

Method plotProbabilityMatrix()

Usage

SurvivalProcessingPipeline$plotProbabilityMatrix(
  surfacesDf,
  distr,
  pExpr = "p"
)

---

Method clone()

The objects of this class are cloneable with this method.

Usage

SurvivalProcessingPipeline$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

terminological/uk-covid-datatools documentation built on June 24, 2021, 8:16 p.m.