pretty_bayesian_regression_tests: Fancy Table of Tests of Bayesian Linear and Logistic...
In z2thet/MoffittFunctions: Moffitt Functions

Description Usage Arguments Details Value Examples

pretty_bayesian_regression_tests takes a stanreg fit object ( family = binomial or guassian), and conducts tests

1	pretty_bayesian_regression_tests(fit, model_data)

`fit`	stanreg (currently only tested on linear model and logistic stan_glm fit)
`model_data`	data.frame or tibble used to create model fits. Used for capturing variable labels, if they exist

Model type is determined by fit class, and also family if. If family is binomial, then the output is designed for a Logistic model (i.e. Odd Ratios), otherwise the output is designed for a linear model.

A tibble with: Mean Est/OR/HR(CI), pd (probabiity of direction), ROPE (CI) (R.O.P.E and CI), 2.5 (R.O.P.E.

# Basic linear model example
set.seed(542542522)
ybin <- sample(0:1, 100, replace = TRUE)
y <- rexp(100,.1)
x1 <- rnorm(100)
x2 <- y + rnorm(100)
x3 <- factor(sample(letters[1:4],100,replace = TRUE))
my_data <- data.frame(y, ybin, x1, x2, x3)
library(rstanarm)
lm_fit <- stan_glm(y ~ x1+ x2 + x3, data = my_data )
pretty_bayesian_regression_tests(fit = lm_fit, model_data = my_data)

library(dplyr)
# Logistic Regression
my_fit <- stan_glm(ybin ~ x1 + x2 + x3, data = my_data, family = binomial)
my_pretty_model_output_tests <-pretty_bayesian_regression_tests(fit = my_fit, model_data = my_data)

# Printing of Fancy table in HTML

kableExtra::kable(my_pretty_model_output_tests, 'html', caption = 'My Table') %>% 
   kableExtra::collapse_rows(c(1:2), row_group_label_position = 'stack')