Description Usage Arguments Details Value See Also Examples
View source: R/add_quantile_glmer.R
This function is one of the methods for add_pi
, and is
called automatically when add_pi
is used on a fit
of
class glmerMod
. This function is experimental.
1 2 3 4 5 6 7 8 9 10 11 12 |
df |
A data frame of new data. |
fit |
An object of class |
p |
A real number between 0 and 1. Sets the probability level of the quantiles. |
name |
|
yhatName |
|
type |
A string. Must be |
includeRanef |
A logical. Default is |
nSims |
A positive integer. Controls the number of bootstrap replicates. |
... |
Additional arguments. |
If IncludeRanef
is False, random slopes and intercepts are set to 0. Unlike in
'lmer' fits, settings random effects to 0 does not mean they are marginalized out. Consider
generalized estimating equations if this is desired.
A dataframe, df
, with predicted values and quantiles attached.
add_pi.glmerMod
for prediction intervals
of glmerMod
objects, add_probs.glmerMod
for
conditional probabilities of glmerMod
objects, and
add_ci.glmerMod
for confidence intervals of
glmerMod
objects.
1 2 3 4 5 6 7 8 | n <- 300
x <- runif(n)
f <- factor(sample(1:5, size = n, replace = TRUE))
y <- rpois(n, lambda = exp(1 - 0.05 * x * as.numeric(f) + 2 * as.numeric(f)))
df <- data.frame(x = x, f = f, y = y)
fit <- lme4::glmer(y ~ (1+x|f), data=df, family = "poisson")
add_quantile(df, fit, name = "quant0.6", p = 0.6, nSims = 500)
|
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