Tidying method for a Lognormal Mixture model (fitted via Expectation-Maximization algorithm).

These method tidy the estimates from survival_ln_mixture fits into a short summary. It doesn't contain uncertainty estimates since it's a likelihood maximization algorithm.

Usage

# S3 method for class 'survival_ln_mixture_em'
tidy(x, effects = "fixed", digits = NULL, ...)

Arguments

x: Fitted model object (survival_ln_mixture_em).
effects: A character vector including one or more of "fixed" and "auxiliary.
digits: How many significant digits should be displayed?
...: Not used.

Value

A data.frame without rownames. When effects="fixed" (the default), tidy.survival_ln_mixutre returns one row for each coefficient for each component of the mixture with two columns:

term: The name of the corresponding term in the model.
estimate: A point estimate of the coefficient (last iteration value).

Setting effects="auxiliary" will select the precision and proportion of mixture components parameters.

Examples


require(survival)
lung$sex <- factor(lung$sex)
set.seed(1)
mod2 <- survival_ln_mixture_em(Surv(time, status == 2) ~ sex, lung)
tidy(mod2)
#> # A tibble: 4 × 2
#>   term          estimate
#>   <chr>            <dbl>
#> 1 (Intercept)_1    4.11 
#> 2 sex2_1           0.941
#> 3 (Intercept)_2    5.74 
#> 4 sex2_2           0.374
tidy(mod2, effects = c("fixed", "auxiliary"))
#> # A tibble: 8 × 2
#>   term          estimate
#>   <chr>            <dbl>
#> 1 (Intercept)_1    4.11 
#> 2 sex2_1           0.941
#> 3 (Intercept)_2    5.74 
#> 4 sex2_2           0.374
#> 5 phi_1            0.676
#> 6 phi_2            2.25 
#> 7 eta_1            0.199
#> 8 eta_2            0.801