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regport (version 0.3.1)

REGModelList: R6 class representing a list of regression model

Description

Contains fields storing data and methods to build, process and visualize a list of regression model. Currently, this class is designed for CoxPH and GLM regression models.

Arguments

Public fields

data

a data.table storing modeling data.

x

focal variables (terms).

y

predicted variables or expression.

covars

covariables.

mlist

a list of REGModel.

args

other arguments used for building model.

type

model type (class).

result

model result, a object of parameters_model. Can be converted into data.frame with as.data.frame() or data.table::as.data.table().

forest_data

more detailed data used for plotting forest.

Methods

Method new()

Create a REGModelList object.

Usage

REGModelList$new(data, y, x, covars = NULL)

Arguments

data

a data.table storing modeling data.

y

predicted variables or expression.

x

focal variables (terms).

covars

covariables.

Returns

a REGModelList R6 object.

Method build()

Build REGModelList object.

Usage

REGModelList$build(
  f = c("coxph", "binomial", "gaussian", "Gamma", "inverse.gaussian", "poisson", "quasi",
    "quasibinomial", "quasipoisson"),
  exp = NULL,
  ci = 0.95,
  parallel = FALSE,
  ...
)

Arguments

f

a length-1 string specifying modeling function or family of glm(), default is 'coxph'. Other options are members of GLM family, see stats::family(). 'binomial' is logistic, and 'gaussian' is linear.

exp

logical, indicating whether or not to exponentiate the the coefficients.

ci

confidence Interval (CI) level. Default to 0.95 (95%). e.g. survival::coxph().

parallel

if TRUE, use N-1 cores to run the task.

...

other parameters passing to corresponding regression model function.

Returns

a REGModel R6 object.

Method plot_forest()

plot forest.

Usage

REGModelList$plot_forest(
  ref_line = NULL,
  xlim = NULL,
  vars = NULL,
  p = NULL,
  ...
)

Arguments

ref_line

reference line, default is 1 for HR.

xlim

limits of x axis.

vars

selected variables to show.

p

selected variables with level' pvalue lower than p.

...

other plot options passing to forestploter::forest(). Also check https://github.com/adayim/forestploter to see more complex adjustment of the result plot.

Method print()

print the REGModelList object

Usage

REGModelList$print(...)

Arguments

...

unused.

Method clone()

The objects of this class are cloneable with this method.

Usage

REGModelList$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

Run this code
ml <- REGModelList$new(
  data = mtcars,
  y = "mpg",
  x = c("factor(cyl)", colnames(mtcars)[3:5]),
  covars = c(colnames(mtcars)[8:9], "factor(gear)")
)
ml
ml$print()
ml$plot_forest()

ml$build(f = "gaussian")
if (FALSE) {
ml$build(f = "gaussian", parallel = TRUE)
}
ml$print()
ml$result
ml$forest_data
ml$plot_forest()

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