Define_sVar: Class for defining and evaluating user-specified summary...

In simcausal: Simulating Longitudinal Data with Causal Inference Applications

Class for defining and evaluating user-specified summary measures (exprs_list)

Description

Evaluates and and stores arbitrary summary measure expressions. The expressions (exprs_list) are evaluated in the environment of the input data.frame.

Format

An R6 class object.

Details

Following fields are created during initialization

• nodes ...

• subset_regs ...

• sA_nms ...

• sW_nms ...

• Kmax ...

Methods

Public methods

• Define_sVar$new()

• Define_sVar$set.new.exprs()

• Define_sVar$eval.nodeforms()

• Define_sVar$eval.EFU()

• Define_sVar$df.names()

• Define_sVar$setnode.setenv()

• Define_sVar$set.net()

• Define_sVar$clone()

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Method new()

Usage

Define_sVar$new()

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Method set.new.exprs()

Usage

Define_sVar$set.new.exprs(exprs_list)

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Method eval.nodeforms()

Usage

Define_sVar$eval.nodeforms(cur.node, data.df)

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Method eval.EFU()

Usage

Define_sVar$eval.EFU(cur.node, data.df)

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Method df.names()

Usage

Define_sVar$df.names(data.df)

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Method setnode.setenv()

Usage

Define_sVar$setnode.setenv(cur.node)

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Method set.net()

Usage

Define_sVar$set.net(netind_cl)

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Method clone()

The objects of this class are cloneable with this method.

Usage

Define_sVar$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

simcausal documentation built on Oct. 29, 2022, 1:13 a.m.