Plot method for model parameters
Source:R/plot.parameters_model.R
, R/plot.parameters_sem.R
plot.see_parameters_model.Rd
The plot()
method for the parameters::model_parameters()
function.
Usage
# S3 method for class 'see_parameters_model'
plot(
x,
show_intercept = FALSE,
size_point = 0.8,
size_text = NA,
sort = NULL,
n_columns = NULL,
type = c("forest", "funnel"),
weight_points = TRUE,
show_labels = FALSE,
show_estimate = TRUE,
show_interval = TRUE,
show_density = FALSE,
log_scale = FALSE,
...
)
# S3 method for class 'see_parameters_sem'
plot(
x,
data = NULL,
component = c("regression", "correlation", "loading"),
type = component,
threshold_coefficient = NULL,
threshold_p = NULL,
ci = TRUE,
size_point = 22,
...
)
Arguments
- x
An object.
- show_intercept
Logical, if
TRUE
, the intercept-parameter is included in the plot. By default, it is hidden because in many cases the intercept-parameter has a posterior distribution on a very different location, so density curves of posterior distributions for other parameters are hardly visible.- size_point
Numeric specifying size of point-geoms.
- size_text
Numeric value specifying size of text labels.
- sort
The behavior of this argument depends on the plotting contexts.
Plotting model parameters: If
NULL
, coefficients are plotted in the order as they appear in the summary. Settingsort = "ascending"
orsort = "descending"
sorts coefficients in ascending or descending order, respectively. Settingsort = TRUE
is the same assort = "ascending"
.Plotting Bayes factors: Sort pie-slices by posterior probability (descending)?
- n_columns
For models with multiple components (like fixed and random, count and zero-inflated), defines the number of columns for the panel-layout. If
NULL
, a single, integrated plot is shown.- type
Character indicating the type of plot. Only applies for model parameters from meta-analysis objects (e.g. metafor).
- weight_points
Logical. If
TRUE
, for meta-analysis objects, point size will be adjusted according to the study-weights.- show_labels
Logical. If
TRUE
, text labels are displayed.- show_estimate
Should the point estimate of each parameter be shown? (default:
TRUE
)- show_interval
Should the compatibility interval(s) of each parameter be shown? (default:
TRUE
)- show_density
Should the compatibility density (i.e., posterior, bootstrap, or confidence density) of each parameter be shown? (default:
FALSE
)- log_scale
Should exponentiated coefficients (e.g., odds-ratios) be plotted on a log scale? (default:
FALSE
)- ...
Arguments passed to or from other methods.
- data
The original data used to create this object. Can be a statistical model.
- component
Character indicating which component of the model should be plotted.
- threshold_coefficient
Numeric, threshold at which value coefficients will be displayed.
- threshold_p
Numeric, threshold at which value p-values will be displayed.
- ci
Logical, whether confidence intervals should be added to the plot.
Examples
library(parameters)
m <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
result <- model_parameters(m)
result
#> Parameter | Coefficient | SE | 95% CI | t(27) | p
#> ------------------------------------------------------------------
#> (Intercept) | 43.54 | 4.86 | [33.57, 53.51] | 8.96 | < .001
#> wt | -3.79 | 1.08 | [-6.01, -1.57] | -3.51 | 0.002
#> cyl | -1.78 | 0.61 | [-3.04, -0.52] | -2.91 | 0.007
#> gear | -0.49 | 0.79 | [-2.11, 1.13] | -0.62 | 0.540
#> disp | 6.94e-03 | 0.01 | [-0.02, 0.03] | 0.58 | 0.568
#>
#> Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
#> using a Wald t-distribution approximation.
plot(result)