itsadug (version 1.0.1)

get_difference: Get model predictions for differences between conditions.

Description

Get model predictions for differences between conditions.

Usage

get_difference(model, comp, cond = NULL, rm.ranef = NULL, se = TRUE,
  f = 1.96, print.summary = getOption("itsadug_print"))

Arguments

model

A gam object, produced by gam or bam.

comp

A named list with the two levels to compare.

cond

A named list of the values to use for the other predictor terms. Variables omitted from this list will have the closest observed value to the median for continuous variables, or the reference level for factors.

rm.ranef

Logical: whether or not to remove random effects. Default is FALSE. Alternatively a string (or vector of strings) with the name of the random effect(s) to remove. (See notes.)

se

Logical: whether or not to return the confidence interval or standard error around the estimates.

f

A number to scale the standard error. Defaults to 1.96, resulting in 95% confidence intervals. For 99% confidence intervals use a value of 2.58.

print.summary

Logical: whether or not to print a summary of the values selected for each predictor. Default set to the print info messages option (see infoMessages).

Value

• Returns a data frame with the estimates of the difference and optionally the confidence intervals around that estimate.

Notes

Other, not specified effects and random effects are generally canceled out, when calculating the difference. When the predictors that specify the conditions to compare are involved in other interactions or included as random slopes, it may be useful to specify the values of other predictors with cond or remove the random effects with rm.ranef.

See Also

Other functions for model predictions: get_coefs; get_modelterm; get_predictions; get_random; inspect_random; plotsurface

Examples

data(simdat)

# first fit a simple model:
m1 <- bam(Y ~ Group+te(Time, Trial, by=Group), data=simdat)

# get difference estimates:
diff <- get_difference(m1, comp=list(Group=c('Adults', 'Children')),
    cond=list(Time=seq(0,500,length=100)))
head(diff)