expertsurv (version 1.4.1)

model.fit.plot: Graphical representation of the measures of model fitting based on Information Criteria

Description

Plots a summary of the model fit for all the models fitted.

Usage

model.fit.plot(..., type = "dic")

Value

A plot with the relevant model fitting statistics plotted in order of fit.

Arguments

...

Optional inputs. Must include an expertsurv object.

type

should the DIC, WAIC, PML be plotted (AIC, BIC also allowed but only valid for frequentist approach).

Examples

require("dplyr")
param_expert_example1 <- list()
param_expert_example1[[1]] <- data.frame(dist = c("norm"),
                                         wi = c(1), # Ensure Weights sum to 1
                                         param1 = c(0.1),
                                         param2 = c(0.05),
                                         param3 = c(NA))
timepoint_expert <- 14 # Expert opinion at t = 14


data2 <- expertsurv::data %>% rename(status = censored) %>% 
mutate(time2 = ifelse(time > 10, 10, time),
status2 = ifelse(time> 10, 0, status))
example1  <- fit.models.expert(formula=Surv(time2,status2)~1,data=data2,
                              distr=c("wei", "gomp"),
                              method="mle",
                              pool_type = "linear pool", 
                              opinion_type = "survival",
                              times_expert = timepoint_expert, 
                              param_expert = param_expert_example1)


model.fit.plot(example1, type = "aic")