In nim-ach/seasonalSensitivity: Data and analysis from the seasonal sensitivity study

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  message = FALSE,
  warning = FALSE,
  fig.align = "center"
)

library(data.table)
library(correlation)
library(kableExtra)
library(seasonalSensitivity)

variables_numericas <- dataset[,
  # Botamos la variable ID (no nos sirve ahora)
  .SD[, -c("id")],
  # Seleccionamos las variables numéricas
  .SDcols = is.numeric]

Veamos todas las correlaciones de manera gráfica.

# Generamos las correlaciones
cor_table <- correlation::correlation(variables_numericas, method = "spearman", p_adjust = "none")

# Redondeamos a los tres decimales los valores numéricos
cor_table <- as.data.frame(cor_table) |> as.data.table()
cor_table[, 3:8 := lapply(.SD, round, digits = 3), .SDcols = 3:8]

# Seleccionamos las variables a presentar
cor_table <- cor_table[, .(
      `Parámetro 1` = Parameter1, 
      `Parámetro 2` = Parameter2, 
      rho = rho, 
      `CI low` = CI_low, 
      `CI high` = CI_high, 
      `p-value` = p, 
      n = n_Obs
    )][order(-`p-value`)]

# Armamos una tabla
tbl <- kable(cor_table)
kable_styling(tbl, bootstrap_options = c("condensed", "responsive", "hover"))

nim-ach/seasonalSensitivity documentation built on July 25, 2024, 1:03 p.m.