Prints tables (i.e. data frame) in different output formats.
print_md() is an alias for display(format = "markdown"), print_html()
is an alias for display(format = "html"). print_table() is for specific
use cases only, and currently only works for compare_parameters() objects.
# S3 method for parameters_model
display(
object,
format = "markdown",
pretty_names = TRUE,
split_components = TRUE,
select = NULL,
caption = NULL,
subtitle = NULL,
footer = NULL,
align = NULL,
digits = 2,
ci_digits = digits,
p_digits = 3,
footer_digits = 3,
ci_brackets = c("(", ")"),
show_sigma = FALSE,
show_formula = FALSE,
zap_small = FALSE,
font_size = "100%",
line_padding = 4,
column_labels = NULL,
include_reference = FALSE,
verbose = TRUE,
...
)# S3 method for parameters_sem
display(
object,
format = "markdown",
digits = 2,
ci_digits = digits,
p_digits = 3,
ci_brackets = c("(", ")"),
...
)
# S3 method for parameters_efa_summary
display(object, format = "markdown", digits = 3, ...)
# S3 method for parameters_efa
display(
object,
format = "markdown",
digits = 2,
sort = FALSE,
threshold = NULL,
labels = NULL,
...
)
# S3 method for equivalence_test_lm
display(object, format = "markdown", digits = 2, ...)
print_table(x, digits = 2, p_digits = 3, theme = "default", ...)
If format = "markdown", the return value will be a character
vector in markdown-table format. If format = "html", an object of
class gt_tbl. For print_table(), an object of class tinytable is
returned.
An object returned by model_parameters(),simulate_parameters(),
equivalence_test() or principal_components().
String, indicating the output format. Can be "markdown"
or "html".
Can be TRUE, which will return "pretty" (i.e. more human
readable) parameter names. Or "labels", in which case value and variable
labels will be used as parameters names. The latter only works for "labelled"
data, i.e. if the data used to fit the model had "label" and "labels"
attributes. See also section Global Options to Customize Messages when Printing.
Logical, if TRUE (default), For models with
multiple components (zero-inflation, smooth terms, ...), each component is
printed in a separate table. If FALSE, model parameters are printed
in a single table and a Component column is added to the output.
Determines which columns and and which layout columns are printed. There are three options for this argument:
Selecting columns by name or index
select can be a character vector (or numeric index) of column names that
should be printed. There are two pre-defined options for selecting columns:
select = "minimal" prints coefficients, confidence intervals and p-values,
while select = "short" prints coefficients, standard errors and p-values.
A string expression with layout pattern
select is a string with "tokens" enclosed in braces. These tokens will
be replaced by their associated columns, where the selected columns will
be collapsed into one column. However, it is possible to create multiple
columns as well. Following tokens are replaced by the related coefficients
or statistics: {estimate}, {se}, {ci} (or {ci_low} and {ci_high}),
{p} and {stars}. The token {ci} will be replaced by {ci_low}, {ci_high}.
Furthermore, a | separates values into new cells/columns. If
format = "html", a <br> inserts a line break inside a cell. See
'Examples'.
A string indicating a pre-defined layout
select can be one of the following string values, to create one of the
following pre-defined column layouts:
"ci": Estimates and confidence intervals, no asterisks for p-values.
This is equivalent to select = "{estimate} ({ci})".
"se": Estimates and standard errors, no asterisks for p-values. This is
equivalent to select = "{estimate} ({se})".
"ci_p": Estimates, confidence intervals and asterisks for p-values. This
is equivalent to select = "{estimate}{stars} ({ci})".
"se_p": Estimates, standard errors and asterisks for p-values. This is
equivalent to select = "{estimate}{stars} ({se})"..
"ci_p2": Estimates, confidence intervals and numeric p-values, in two
columns. This is equivalent to select = "{estimate} ({ci})|{p}".
"se_p2": Estimate, standard errors and numeric p-values, in two columns.
This is equivalent to select = "{estimate} ({se})|{p}".
For model_parameters(), glue-like syntax is still experimental in the
case of more complex models (like mixed models) and may not return expected
results.
Table caption as string. If NULL, depending on the model,
either a default caption or no table caption is printed. Use caption = ""
to suppress the table caption.
Table title (same as caption) and subtitle, as strings. If NULL,
no title or subtitle is printed, unless it is stored as attributes (table_title,
or its alias table_caption, and table_subtitle). If x is a list of
data frames, caption may be a list of table captions, one for each table.
Can either be FALSE or an empty string (i.e. "") to
suppress the footer, NULL to print the default footer, or a string. The
latter will combine the string value with the default footer.
Only applies to HTML tables. May be one of "left",
"right" or "center".
Number of digits for rounding or
significant figures. May also be "signif" to return significant
figures or "scientific" to return scientific notation. Control the
number of digits by adding the value as suffix, e.g. digits = "scientific4"
to have scientific notation with 4 decimal places, or digits = "signif5"
for 5 significant figures (see also signif()).
Number of decimal places for values in the footer summary.
Logical, if TRUE (default), CI-values are
encompassed in square brackets (else in parentheses).
Logical, if TRUE, adds information about the residual
standard deviation.
Logical, if TRUE, adds the model formula to the output.
Logical, if TRUE, small values are rounded after
digits decimal places. If FALSE, values with more decimal
places than digits are printed in scientific notation.
For HTML tables, the font size.
For HTML tables, the distance (in pixel) between lines.
Labels of columns for HTML tables. If NULL, automatic
column names are generated. See 'Examples'.
Logical, if TRUE, the reference level of factors will
be added to the parameters table. This is only relevant for models with
categorical predictors. The coefficient for the reference level is always
0 (except when exponentiate = TRUE, then the coefficient will be 1),
so this is just for completeness.
Toggle messages and warnings.
Arguments passed to or from other methods.
Sort the loadings.
A value between 0 and 1 indicates which (absolute) values
from the loadings should be removed. An integer higher than 1 indicates the
n strongest loadings to retain. Can also be "max", in which case it
will only display the maximum loading per variable (the most simple
structure).
A character vector containing labels to be added to the loadings data. Usually, the question related to the item.
An object returned by model_parameters().
String, indicating the table theme. Can be one of "default",
"grid", "striped", "bootstrap" or "darklines".
display() is useful when the table-output from functions,
which is usually printed as formatted text-table to console, should
be formatted for pretty table-rendering in markdown documents, or if
knitted from rmarkdown to PDF or Word files. See
vignette
for examples.
print_table() is a special function for compare_parameters() objects,
which prints the output as a formatted HTML table. It is still somewhat
experimental, thus, only a fixed layout-style is available at the moment
(columns for estimates, confidence intervals and p-values). However, it
is possible to include other model components, like zero-inflation, or random
effects in the table. See 'Examples'. An alternative is to set engine = "tt"
in print_html() to use the tinytable package for creating HTML tables.
print.parameters_model() and print.compare_parameters()
if (FALSE) { # require("gt", quietly = TRUE)
model <- lm(mpg ~ wt + cyl, data = mtcars)
mp <- model_parameters(model)
display(mp)
# \donttest{
data(iris)
lm1 <- lm(Sepal.Length ~ Species, data = iris)
lm2 <- lm(Sepal.Length ~ Species + Petal.Length, data = iris)
lm3 <- lm(Sepal.Length ~ Species * Petal.Length, data = iris)
out <- compare_parameters(lm1, lm2, lm3)
print_html(
out,
select = "{coef}{stars}|({ci})",
column_labels = c("Estimate", "95% CI")
)
# line break, unicode minus-sign
print_html(
out,
select = "{estimate}{stars}({ci_low} \u2212 {ci_high})",
column_labels = c("Est. (95% CI)")
)
# }
}
if (FALSE) { # require("tinytable") && require("lme4") && require("glmmTMB")
# \donttest{
data(iris)
data(Salamanders, package = "glmmTMB")
m1 <- lm(Sepal.Length ~ Species * Petal.Length, data = iris)
m2 <- lme4::lmer(
Sepal.Length ~ Petal.Length + Petal.Width + (1 | Species),
data = iris
)
m3 <- glmmTMB::glmmTMB(
count ~ spp + mined + (1 | site),
ziformula = ~mined,
family = poisson(),
data = Salamanders
)
out <- compare_parameters(m1, m2, m3, effects = "all", component = "all")
print_table(out)
# }
}
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