JAB {alphaN}  R Documentation 
Transforms a tstatistic from a glm or lm object into Jeffreys' approximate Bayes factor
Description
Transforms a tstatistic from a glm or lm object into Jeffreys' approximate Bayes factor
Usage
JAB(glm_obj, covariate, method = "JAB", upper = 1)
Arguments
glm_obj 
a glm or lm object. 
covariate 
the name of the covariate that you want a BF for as a string. 
method 
Used for the choice of 'b'. Currently one of:

upper 
The upper limit for the range of realistic effect sizes. Only relevant when method="balanced". Defaults to 1 such that the range of realistic effect sizes is uniformly distributed between 0 and 1, U(0,1). 
Value
A numeric value for the BF in favour of H1.
Examples
# Simulate data
## Sample size
n < 200
## Regressors
Z1 < runif(n, 1, 1)
Z2 < runif(n, 1, 1)
Z3 < runif(n, 1, 1)
Z4 < runif(n, 1, 1)
X < runif(n, 1, 1)
## Error term
U < rnorm(n, 0, 0.5)
## Outcome
Y < X/sqrt(n) + U
# Run a GLM
LM < glm(Y ~ X + Z1 + Z2 + Z3 + Z4)
# Compute JAB for "X" based on the regression results
JAB(LM, "X")
# Compute JAB using the minimum prior
JAB(LM, "X", method = "min")