inst/doc/invest-spec.R

In specr: Conducting and Visualizing Specification Curve Analyses

## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  #fig.path = "man/figures/README-",
  out.width = "100%",
  fig.retina = 2
)

## ---- message = F, warning = F------------------------------------------------
library(tidyverse)
library(specr)
library(performance)

## ---- message=F, warning = F--------------------------------------------------
# Custom function
tidy_new <- function(x) {
  fit <- broom::tidy(x, conf.int = TRUE)
  fit$res <- list(x)  # Store model object
  return(fit)
}

# Run specification curve analysis
specs <- setup(data = example_data, 
               y = c("y1", "y2"), 
               x = c("x1", "x2"), 
               model = c("lm"),
               controls = c("c1", "c2"),
               subsets = list(group1 = unique(example_data$group1),  
                              group2 = unique(example_data$group2)),
               fun1 = tidy_new)

results <- specr(specs)

## -----------------------------------------------------------------------------
(y_models <- results %>%
  as_tibble %>%
  filter(x == "x1", 
         controls == "c1 + c2",
         subsets == "all")) %>%
  select(x:group2, estimate:res)

## -----------------------------------------------------------------------------
y_models %>%
  pull(res) %>%
  map(summary) %>%
  map(coef)

## -----------------------------------------------------------------------------
y_models %>%
  pull(res) %>% 
  map(r2)       # r2 is include in the package "performance"

## ---- fig.height=8, fig.width=10, message=F, warning = F----------------------
r2_results <- results %>%
  as_tibble %>%
  filter(subsets == "all") %>%
  mutate(r2 = map(res, r2), 
         r2 = map_dbl(r2, 1)) %>%
  arrange(r2)

r2_results %>%
  select(x:controls, r2)

## -----------------------------------------------------------------------------
r2_results %>%
  arrange(r2) %>%
  mutate(rank = 1:n()) %>%
  ggplot(aes(x = rank, 
             y = r2)) +
  geom_point() +
  geom_line() +
  theme_minimal() +
  theme(strip.text = element_blank(),
        axis.line = element_line("black", size = .5),
        axis.text = element_text(colour = "black"))