diagnostic_plot: Create diagnostic plots

In gompertztrunc: Conducting Maximum Likelihood Estimation with Truncated Mortality Data

Create diagnostic plots

Description

Compare empirical and modeled distribution of ages of death within a cohort. Only works with a single discrete covariate and a single cohort.

Usage

diagnostic_plot(
  data,
  object,
  covar,
  death_var = "death_age",
  byear_var = "byear",
  xlim = c(65, 110)
)

Arguments

data	data used to create gompertz_mle object
object	gompertz_mle object
covar	covariate of interest
death_var	death age variable
byear_var	birth year/cohort variable
xlim	x-limits for figure

Value

a ggplot object

Examples

# Create a single-cohort data set
numident_c1920 <- numident_demo %>% dplyr::filter(byear == 1920) %>%
dplyr::mutate(finished_hs = as.factor(educ_yrs >= 12))

# Run gompertz_mle()
gradient <- gompertztrunc::gompertz_mle(formula = death_age ~ finished_hs,
left_trunc = 1988, right_trunc = 2005, data = numident_c1920)

# Create diagnostic histogram plot using model outcome
gompertztrunc::diagnostic_plot(object = gradient, data = numident_c1920,
covar = "finished_hs", xlim = c(60, 95))

gompertztrunc documentation built on May 29, 2024, 4:56 a.m.