Description Usage Arguments Value Examples
This function plots ROC curves across group - outcome - stat combinations
and currently supports stat_glm
.
1 | aba_plot_roc(object)
|
object |
abaSummary. A summary of an aba model with |
a ggplot with roc curves for all predictor sets across each group - outcome - stat combination
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | data <- adnimerge %>% dplyr::filter(VISCODE == 'bl')
# fit glm model with binary outcome variables
model <- data %>% aba_model() %>%
set_groups(everyone()) %>%
set_outcomes(ConvertedToAlzheimers, CSF_ABETA_STATUS_bl) %>%
set_predictors(
PLASMA_ABETA_bl, PLASMA_PTAU181_bl, PLASMA_NFL_bl,
c(PLASMA_ABETA_bl, PLASMA_PTAU181_bl, PLASMA_NFL_bl)
) %>%
set_stats(
stat_glm(std.beta = TRUE)
) %>%
fit()
# summarise glm model
model_summary <- model %>% summary()
fig <- model_summary %>% aba_plot_roc()
|
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