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Plot the Output of 'loglike_compare()'

Source: R/loglike_at.R
plot.loglike_compare.Rd

Visualize the log profile likelihood of a parameter fixed to values in a range.

Usage

# S3 method for loglike_compare
plot(
  x,
  y,
  type = c("ggplot2", "default"),
  size_label = 4,
  size_point = 4,
  nd_theta = 3,
  nd_pvalue = 3,
  size_theta = 4,
  size_pvalue = 4,
  add_pvalues = FALSE,
  ...
)

Arguments

x

The output of loglike_compare().

y

Not used.

type

Character. If "ggplot2", will use ggplot2::ggplot() to plot the graph. If "default", will use R base graphics, The ggplot2 version plots more information. Default is "ggplot2".

size_label

The relative size of the labels for thetas (and p-values, if requested) in the plot, determined by ggplot2::rel(). Default is 4.

size_point

The relative size of the points to be added if p-values are requested in the plot, determined by ggplot2::rel(). Default is 4.

nd_theta

The number of decimal places for the labels of theta. Default is 3.

nd_pvalue

The number of decimal places for the labels of p-values. Default is 3.

size_theta

Deprecated. No longer used.

size_pvalue

Deprecated. No longer used.

add_pvalues

If TRUE, likelihood ratio test p-values will be included for the confidence limits. Only available if type = "ggplot2".

...

Optional arguments. Ignored.

Value

Nothing if type = "default", the generated ggplot2::ggplot()

graph if type = "ggplot2".

Details

Given the output of loglike_compare(), it plots the log profile likelihood based on quadratic approximation and that based on the original log-likelihood. The log profile likelihood is scaled to have a maximum of zero (at the point estimate) as suggested by Pawitan (2013).

References

Pawitan, Y. (2013). In all likelihood: Statistical modelling and inference using likelihood. Oxford University Press.

Examples


## loglike_compare

library(lavaan)
data(simple_med)
dat <- simple_med
mod <-
"
m ~ a * x
y ~ b * m
ab := a * b
"
fit <- lavaan::sem(mod, simple_med, fixed.x = FALSE)

# Four points are used just for illustration
# At least 21 points should be used for a smooth plot
# Remove try_k_more in real applications. It is set
# to run such that this example is not too slow.
# use_pbapply can be removed or set to TRUE to show the progress.
ll_a <- loglike_compare(fit, par_i = "m ~ x", n_points = 4,
                        try_k_more = 0,
                        use_pbapply = FALSE)

plot(ll_a)

plot(ll_a, add_pvalues = TRUE)


# See the vignette "loglike" for an example for the
# indirect effect.