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#' Plot Power Curve for Subgroup analysis
#'
#' Plots power curves to detect subgroup differences in meta-analysis.
#'
#' @export
#'
#' @param obj This should be an 'subgroup_power' object
#'
#' @return Power curves to detect subgroup differences for fixed and random effects models
plot_subgroup_power <- function(obj){
if(class(obj) != "subgroup_power")
stop("Object must be of class: subgroup_power")
## set aesthetic
p_aes <- list(geom_hline(yintercept = .80, linetype = "dashed", alpha = .80),
geom_line(size = 1.5),
scale_x_continuous(limits = c(2,max(obj$subgroup_power_range$k_v)), breaks = c(seq(2,max(obj$subgroup_power_range$k_v),by = round(max(obj$subgroup_power_range$k_v)*.10,0)))),
scale_y_continuous(limits =c(0,1), breaks = c(0,.20,.40,.60,.80,1)),
xlab("Number of Studies"),
ylab("Power"),
theme_bw(),
theme(legend.position = c(1,0),
legend.justification = c(1,0),
legend.background = element_rect(colour = 'black', fill = 'white', linetype='solid')))
return(ggplot(obj$subgroup_power_range %>% tidyr::pivot_longer(c("fixed_power_b", "random_power_b"), names_to = "power_type", values_to = "power"),
aes(x = .data$k_v, y = .data$power, color = .data$power_type)) + p_aes +
geom_point(aes(x = obj$k, y = obj$subgroup_power$fixed_power_b),shape = 21, size = 3, fill = "white", color = "#993366", stroke = 1) +
geom_point(aes(x = obj$k, y = obj$subgroup_power$random_power_b),shape = 21, size = 3, fill = "white",color = "#33CCCC", stroke = 1) +
ggtitle("Power Analysis for Subgroup Analysis") +
scale_color_manual(name = paste0("Supgroup Analysis (",obj$n_groups, " subgroups)"),
labels = c("Fixed Effects", paste0("Random Effects (I2 = ",round(obj$i2*100,2), "%)")),
values = c("#993366", "#33CCCC")))
}
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