LtAtDataInst: Data Storage Class for LtAt dataset based on instant exposure

In romainkp/LtAtStructuR: Structuring of Complex Longitudinal Data into Long Format

Data Storage Class for LtAt dataset based on instant exposure

Description

Class that defines the specifications for constructing an LtAt dataset and the dataset itself using an instant exposure dataset.

Format

R6Class object.

Value

LtAtDataInst object

Fields

data:

data.table containing the LtAt dataset. NULL by default before construction.

cohort_data:

cohortData specifying the cohort dataset.

exp_data:

expData specifying the time-varying exposure dataset. Its IDvar field must contain the same value as that of the cohort_data (i.e., the same column name must be used for the ID column of the exposure and cohort datasets). The unique subject identifiers in the data field of exp_data must be a subset of those founds in the data field of cohort_data (i.e., all IDs in the exposure dataset must also be present in the cohort dataset.) An exposure measurement stored in the data field of exp_data will be ignored if its date is either strictly before the subject's index date stored in the data field of cohort_data or strictly after the subject's end of follow-up date stored in the data field of cohort_data (i.e., only exposure measurements collected between the start and end of follow-up will be retained).

cov_data:

a list of timeDepCovData that specifies time-varying covariate(s). Each element of the list must have a distinct value stored in its L_name field and this value must also be found in the L0 field of cohort_data (i.e., time-varying covariates cannot have the same name and must have their baseline measurements stored in the cohort dataset). The IDvar field of each element timeDepCovData of cov_data must contain the same value as that of the cohort_data (i.e., the same column name must be used for the ID column of each covariate dataset and that of the cohort dataset). The unique subject identifiers in the data field of each element timeDepCovData of cov_data must be a subset of those founds in the data field of cohort_data (i.e., all IDs in a covariate dataset must also be present in the cohort dataset.) A covariate measurement stored in the data field of an element timeDepCovData of cov_data will be ignored if its date is either strictly before the subject's index date stored in the data field of cohort_data or strictly after the subject's end of follow-up date stored in the data field of cohort_data. (i.e., only covariate measurements collected between the start and end of follow-up will be retained).

Super class

LtAtStructuR::LtAtData -> LtAtDataInst

Methods

Public methods

• LtAtDataInst$new()

• LtAtDataInst$copyLtAtData()

• LtAtDataInst$construct()

• LtAtDataInst$setAlgoOptions()

• LtAtDataInst$assignAC()

• LtAtDataInst$assignL()

• LtAtDataInst$cleanUp()

• LtAtDataInst$clone()

Inherited methods

• LtAtStructuR::LtAtData$addSpec()

• LtAtStructuR::LtAtData$createIntervals()

• LtAtStructuR::LtAtData$imputeL()

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Method new()

Usage

LtAtDataInst$new()

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Method copyLtAtData()

Usage

LtAtDataInst$copyLtAtData(LtAtObject)

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Method construct()

Usage

LtAtDataInst$construct(time_unit, ...)

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Method setAlgoOptions()

Usage

LtAtDataInst$setAlgoOptions(time_unit, ...)

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Method assignAC()

Usage

LtAtDataInst$assignAC()

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Method assignL()

Usage

LtAtDataInst$assignL()

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Method cleanUp()

Usage

LtAtDataInst$cleanUp()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LtAtDataInst$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

romainkp/LtAtStructuR documentation built on Aug. 24, 2024, 3:38 p.m.