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Contains covariate data

Source: R/PM_result.R
PM_cov.Rd

[Stable]

Contains a data frame with subject-specific covariate data output from makeCov

Details

For each subject, makeCov extracts covariate information and Bayesian posterior parameter estimates. This output of this function is suitable for exploration of covariate- parameter, covariate-time, or parameter-time relationships.

Author

Michael Neely, Julian Otalvaro

Public fields

data

A data frame with the following columns

  • id Subject identification

  • time Times of covariate observations

  • covnames... Columns with each covariate observations in the dataset for each subject and time

  • parnames... Columns with each parameter in the model and the icen summary for each subject, replicated as necessary for covariate observation times and duplicated for Bayesian parameter means and medians

  • icen The type of summarized Bayesian posterior individual parameter values: mean or median

Methods

Public methods

Method new()

Create new object populated with covariate-parameter information

Usage

PM_cov$new(cov)

Arguments

cov

The parsed output from makeCov.

Details

Creation of new PM_cov object is automatic and not generally necessary for the user to do.

Method step()

Stepwise linear regression of covariates and Bayesian posterior parameter values

Usage

PM_cov$step(...)

Arguments

...

Arguments passed to PMstep

Details

See PMstep.

Method summary()

Summary method

Usage

PM_cov$summary(...)

Arguments

...

Arguments passed to summary.PMcov

Details

See summary.PMcov.

Method plot()

Plot method

Usage

PM_cov$plot(...)

Arguments

...

Arguments passed to plot.PM_cov

Details

See plot.PM_cov.

Method print()

Print method

Usage

PM_cov$print(...)

Arguments

...

Arguments passed to print

Details

Print method for PM_cov

Method clone()

The objects of this class are cloneable with this method.

Usage

PM_cov$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.