Calculate CURE Dataframe

Usage

calculate_cure_dataframe(covariate_values, residuals)

Arguments

covariate_values: name to be plot. With or without quotes.
residuals: Residuals.

Value

A data frame with five columns: independent variable, residuals, cumulative residuals, lower confidence interval limit, and upper confidence interval limit.

Examples

set.seed(2000)

## Define parameters
beta <- c(-1, 0.3, 3)

## Simulate independent variables
n <- 900
AADT <- c(runif(n, min = 2000, max = 150000))
nlanes <- sample(x = c(2, 3, 4), size = n, replace = TRUE)
LNAADT <- log(AADT)

## Simulate dependent variable
theta <- exp(beta[1] + beta[2] * LNAADT + beta[3] * nlanes)
y <- rpois(n, theta)

## Fit model
mod <- glm(y ~ LNAADT + nlanes, family = poisson)

## Calculate residuals
res <- residuals(mod, type = "working")

## Calculate CURE plot data
cure_df <- calculate_cure_dataframe(AADT, res)
#> Covariate: AADT

head(cure_df)
#> # A tibble: 6 × 5
#>    AADT  residual    cumres     lower    upper
#>   <dbl>     <dbl>     <dbl>     <dbl>    <dbl>
#> 1 2363. -0.000379 -0.000379 -0.000743 0.000743
#> 2 2435.  0.0112    0.0108   -0.0219   0.0219  
#> 3 2724.  0.00769   0.0185   -0.0266   0.0266  
#> 4 2978. -0.00233   0.0162   -0.0270   0.0270  
#> 5 3007. -0.0119    0.00424  -0.0356   0.0356  
#> 6 3149. -0.0101   -0.00589  -0.0407   0.0407