Latent Biomarker Construct + Cox Regression — latentbiomarker • ClinicoPath

Estimate a single reflective latent biomarker construct from 3+ indicators and relate it to a right-censored survival outcome via Cox regression. Auto-selects MLR (continuous) or WLSMV (ordinal/binary) estimation. Refuses inappropriate inputs with explanatory messages.

Usage

latentbiomarker(
  data,
  dep_time = NULL,
  dep_event = NULL,
  event_level,
  indicators = NULL,
  adjusters = NULL,
  indicator_types = "auto",
  reflective_confirmed = FALSE,
  factor_score_method = "regression",
  standardize_scores = TRUE,
  factor_score_name = "biomarker_factor",
  km_strata = "tertile",
  show_plot_km = TRUE,
  show_plot_loadings = TRUE,
  show_plot_path = TRUE,
  show_diagnostics = TRUE,
  show_r_code = FALSE
)

Arguments

data: The data as a data frame.
dep_time: .
dep_event: .
event_level: .
indicators: .
adjusters: .
indicator_types: .
reflective_confirmed: .
factor_score_method: .
standardize_scores: .
factor_score_name: .
km_strata: .
show_plot_km: .
show_plot_loadings: .
show_plot_path: .
show_diagnostics: .
show_r_code: .

Value

A results object containing:

`results$notices`					a html
`results$summaryTable`					a table
`results$loadingsTable`					a table
`results$reliabilityTable`					a table
`results$fitTable`					a table
`results$coxTable`					a table
`results$phTable`					a table
`results$kmPlot`					an image
`results$loadingsPlot`					an image
`results$pathPlot`					an image
`results$miTable`					a table
`results$rCode`					a preformatted
`results$save_factor_scores`					an output

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$summaryTable$asDF

as.data.frame(results$summaryTable)