seqER {ESTER} | R Documentation |
Computes sequential evidence ratios
Description
Computes sequential evidence ratios, either based on the AIC or the BIC.
Supported models currently include lm
, merMod
, or brmsfit
models.
When data involve repeated measures (and so multiple lines per subject),
a column indicating the subject "id" should be provided to the id
argument.
If nothing is passed to the id
argument, seqER
will suppose
that there is only one observation (i.e., one line) per subject.
Usage
seqER(ic = bic, mod1, mod2, nmin = 10, id = NULL, boundary = Inf,
blind = FALSE, nsims = NULL)
Arguments
ic |
Indicates whether to use the aic or the bic. |
mod1 |
A model of class |
mod2 |
A model of class |
nmin |
Minimum sample size from which start to compute sequential evidence ratios. |
id |
If applicable (i.e., repeated measures), name of the "id" column of your dataframe, in character string. |
boundary |
The Evidence Ratio (or its reciprocal) at which the run is stopped as well |
blind |
If true, the function only returns a "continue or stop" message |
nsims |
Number of permutation samples to evaluate (is ignored if blind = TRUE) |
Author(s)
Ladislas Nalborczyk <ladislas.nalborczyk@gmail.com>
See Also
Examples
## Not run:
data(mtcars)
mod1 <- lm(mpg ~ cyl, mtcars)
mod2 <- lm(mpg ~ cyl + disp, mtcars)
seqER(ic = bic, mod1, mod2, nmin = 10)
# Example with ten permutation samples
data(mtcars)
mod1 <- lm(mpg ~ cyl, mtcars)
mod2 <- lm(mpg ~ cyl + disp, mtcars)
seqER(ic = bic, mod1, mod2, nmin = 10, nsims = 10)
# Example with blinding
data(mtcars)
mod1 <- lm(mpg ~ cyl, mtcars)
mod2 <- lm(mpg ~ cyl + disp, mtcars)
seqER(ic = bic, mod1, mod2, nmin = 10, boundary = 10, blind = TRUE)
# Example with repeated measures
library(lme4)
data(sleepstudy)
mod1 <- lmer(Reaction ~ Days + (1|Subject), sleepstudy)
mod2 <- lmer(Reaction ~ Days + I(Days^2) + (1|Subject), sleepstudy)
seqER(ic = bic, mod1, mod2, nmin = 10, id = "Subject", nsims = 10)
# Example with brmsfit models
library(brms)
mod1 <- brm(Reaction ~ Days + (1|Subject), sleepstudy)
mod2 <- brm(Reaction ~ Days + I(Days^2) + (1|Subject), sleepstudy)
seqER(ic = WAIC, mod1, mod2, nmin = 10, id = "Subject", nsims = 10)
## End(Not run)