get_difference: Get model predictions for differences between conditions.

In itsadug: Interpreting Time Series and Autocorrelated Data Using GAMMs

Get model predictions for differences between conditions.

Description

Get model predictions for differences between conditions.

Usage

get_difference(
  model,
  comp,
  cond = NULL,
  rm.ranef = TRUE,
  se = TRUE,
  sim.ci = FALSE,
  f = 1.96,
  return.n.posterior = 0,
  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 TRUE. Alternatively a vector of numbers with the mdoelterm number 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.
sim.ci	Logical: Using simultaneous confidence intervals or not (default set to FALSE). The implementation of simultaneous CIs follows Gavin Simpson's blog of December 15, 2016: https://fromthebottomoftheheap.net/2016/12/15/simultaneous-interval-revisited/. This interval is calculated from simulations based. Please specify a seed (e.g., set.seed(123)) for reproducable results. In addition, make sure to specify at least 200 points for each smooth for the simulations when using simultaneous CI. Note: in contrast with Gavin Simpson's code, here the Bayesian posterior covariance matrix of the parameters is uncertainty corrected (unconditional=TRUE) to reflect the uncertainty on the estimation of smoothness parameters.
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.
return.n.posterior	Numeric: N samples from the posterior distribution of the fitted model are returned. Default value is 0 (no samples returned). Only workes when sim.ci=TRUE.
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.

Author(s)

Jacolien van Rij, Martijn Wieling

See Also

Other Model predictions: get_coefs(), get_fitted(), get_modelterm(), get_predictions(), get_random()

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)

itsadug documentation built on June 17, 2022, 5:05 p.m.