The function calculates the (average) predicted value with the confidence interval for a lmer model.
Usage
# S3 method for lmerMod
basepredict(model, values, sim.count=1000, conf.int=0.95, sigma=NULL, set.seed=NULL,
type = c("any", "simulation", "bootstrap"), summary = TRUE)
Value
The output is a 3x3 matrix having in the first column the predicted value, in the second
column the lower value of the confidence interval and in the third column the upper value
of the confidence interval.
Arguments
model
the model Object generated with lmer()
values
the values of the case as vector in the order how they appear in the summary(model) Estimate
sim.count
OPTIONAL numbers of simulations to be done by the function. default: 1000
conf.int
OPTIONAL the confidence interval used by the function. default: 0.95
sigma
OPTIONAL the variance-covariance matrix, can be changed when having for example robust or clustered vcov. default: vcov(model)
set.seed
OPTIONAL set a seed for the random number generator
type
OPTIONAL choose between simulation and bootstrap, "any" chooses between those two
according to the number of cases (bootstrap if n < 1000)
summary
OPTIONAL if mean/quantiles should be return or all simulated values (default: TRUE)
model1 = lme4::lmer(lr_self ~ age + gender + (1 | canton), data=selects2015)
summary(model1)
# predicted left-right position of a 18 year old woman.basepredict(model1, c(1,18,1))