View source: R/as_flextable.cond_indirect_effects.R
as_flextable.cond_indirect_effects | R Documentation |
The 'as_flextable' method for the output of 'manymome::many_indirect_effects()'.
## S3 method for class 'cond_indirect_effects'
as_flextable(
x,
pvalue = FALSE,
se = TRUE,
var_labels = NULL,
digits = 2,
pval_digits = 3,
use_arrow = TRUE,
indirect_raw = TRUE,
indirect_raw_ci = indirect_raw,
indirect_raw_se = indirect_raw,
footnote = TRUE,
show_wvalues = TRUE,
show_indicators = FALSE,
show_path = TRUE,
pcut = 0.001,
...
)
x |
The object to be converted.
Should be of the class |
pvalue |
If bootstrap confidence
intervals are stored, whether
asymmetric p-values are reported.
Default is |
se |
Whether standard errors
are reported if confidence intervals
are stored. Default is |
var_labels |
A named vectors.
Used to replace variable names by
other names when generating the
table. For example,
|
digits |
The number of digits to be displayed for most numerical columns, such as effect estimates, standard errors, and confidence intervals. Default is 2. |
pval_digits |
The number of digits to be displayed for the p-value column, if present. Default is 3. |
use_arrow |
If |
indirect_raw |
If |
indirect_raw_ci |
If |
indirect_raw_se |
If |
footnote |
If |
show_wvalues |
Whether the values
of moderators will be shown. If |
show_indicators |
Whether the values
of indicators (dummy variables) will
be shown for categorical moderators.
Default is |
show_path |
Whether the paths
being moderated will be displayed.
Default is |
pcut |
Any p-value less than
|
... |
Additional arguments. Ignored. |
It converts an cond_indirect_effects
object,
which is usually created by
manymome::cond_indirect_effects()
,
to a flextable
object. The output
can be further modified by functions
from the flextable
package.
A flextable
object.
library(manymome)
library(flextable)
# List of indirect effects
dat <- data_med_mod_a
lm_m <- lm(m ~ x*w + c1 + c2, dat)
lm_y <- lm(y ~ m + x + c1 + c2, dat)
fit_lm <- lm2list(lm_m, lm_y)
# Should set R to 5000 or 10000 in real research
boot_out_lm <- do_boot(fit_lm,
R = 100,
seed = 54532,
parallel = FALSE,
progress = FALSE)
out_xmy_on_w <- cond_indirect_effects(wlevels = "w",
x = "x",
y = "y",
m = "m",
fit = fit_lm,
boot_ci = TRUE,
boot_out = boot_out_lm)
std_xmy_on_w <- cond_indirect_effects(wlevels = "w",
x = "x",
y = "y",
m = "m",
fit = fit_lm,
boot_ci = TRUE,
boot_out = boot_out_lm,
standardized_x = TRUE,
standardized_y = TRUE)
ft1 <- as_flextable(out_xmy_on_w,
var_labels = c(w = "Moderator"))
ft1
ft2 <- as_flextable(std_xmy_on_w,
var_labels = c(w = "Moderator"),
se = FALSE,
digits = 3)
ft2
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