Conditional distribution of Y|T for a mixed continuous/ordinal (Gaussian-copula) joint model, if no competing risk

Copula-aware counterpart to conditionalYT(), used by predictRisk() whenever long_fit_all$biomarker_type contains at least one "ordinal" biomarker (see longitudinalSubCopula()). Continuous biomarkers contribute an exact Gaussian density factor, exactly as conditionalYT() computes for every biomarker; ordinal biomarkers instead contribute a Gaussian-copula box probability (via mixed_density_prob_copula()), since only the cumulative-link category – not the exact underlying latent score – is observed for them. All-continuous fits are unaffected: they are still routed to conditionalYT() by predictRisk(), this function is never called for them, and mixed_density_prob_copula() reduces to (a constant multiple of) conditionalYT()'s own computation when there are no ordinal markers – see that function's documentation.

Usage

conditionalYTCopula(
  data_predict_all,
  long_fit_all,
  l_i,
  survival_variable,
  time_variable,
  survival_variable_all,
  survival_trans_function
)

Arguments

data_predict_all

This involves a collection of data.frame objects for dynamic prediction, each corresponding to a distinct longitudinal outcome. These data frames should contain the variables specified in long_sub_fixed and long_sub_random. Utilizing a list structure allows for the incorporation of multiple longitudinal outcomes, each potentially following different measurement protocols. In instances where all longitudinal outcomes are recorded at identical time points across patients, a singular data.frame object may be used in a list. It is presumed that each data frame is structured in a long format.

long_fit_all

Outputs from the model fitting process using the nlme package, encompassing the results and parameters obtained from the analysis.

l_i

A vector of time points to calculate the conditional probability.

survival_variable

Time-to-event outcomes variable name.

time_variable

The name of time variable in linear mixed model.

survival_variable_all

The name of the transformed time-to-event outcomes variable.

survival_trans_function

The transformation function used for time-to-event outcomes, in the order of survival_variable_all.