Convert an 'cond_indirect_effects' Object to a 'flextable' Object

The 'as_flextable' method for the output of 'manymome::many_indirect_effects()'.

Usage

# 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,
  level = 0.95,
  ...
)

Arguments

x

The object to be converted. Should be of the class cond_indirect_effects from the package manymome.

pvalue

If bootstrap confidence intervals are stored, whether asymmetric p-values are reported. Default is FALSE. See manymome::print.cond_indirect_effects() for the computational details.

se

Whether standard errors are reported if confidence intervals are stored. Default is TRUE. See manymome::print.cond_indirect_effects() for the computation details.

var_labels

A named vectors. Used to replace variable names by other names when generating the table. For example, c(x = "I.V", y = "D.V.") replaces x by "I.V" and y by "D.V." in the output.

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 TRUE, the default, use the arrow symbol in the paths.

indirect_raw

If TRUE, the default, report unstandardized effects even if standardization was done.

indirect_raw_ci

If TRUE, report the confidence intervals of unstandardized effects even if standardization was done and confidence intervals were stored. Default to be equal to indirect_raw. NOTE: Not used for now. Always FALSE.

indirect_raw_se

If TRUE, report the standard errors of unstandardized effects even if standardization was done and confidence intervals were stored. Default to be equal to indirect_raw. NOTE: Not used for now. Always FALSE.

footnote

If TRUE, the default, add footnote(s) regarding the results to the bottom of the table.

show_wvalues

Whether the values of moderators will be shown. If FALSE, no values will be shown, even for categorical moderators. Default is TRUE.

show_indicators

Whether the values of indicators (dummy variables) will be shown for categorical moderators. Default is FALSE.

show_path

Whether the paths being moderated will be displayed. Default is TRUE.

pcut

Any p-value less than pcut will be displayed as <[pcut], "[pcut]" replaced by the value of pcut. Default is .001.

level

The level of confidence for the confidence intervals computed from the original standard errors (e.g., the standard errors in stats::lm() or lavaan). Used only for paths without mediators and both x- and y-variables are not standardized. Default is .95.

...

Additional arguments. To be passed to flextable::autofit() in preparing the final table. For example, if some lines are too lone and wrapped, try adding add_w = .2.

Value

A flextable object.

Details

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.

Examples

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
Path:  x → m → y
[Moderator]
(Moderator)
Effect
95% CI
SE
M+1.0SD
3.16
3.06
[2.17
, 4.04]
0.46
Mean
2.18
2.14
[1.41
, 2.93]
0.36
M-1.0SD
1.19
1.21
[-0.29
, 2.56]
0.59
Note: [w] is the meaning of a level of moderator 'w'; (w) is the value of a level of moderator 'w': CI = confidence interval.

ft2 <- as_flextable(std_xmy_on_w,
                    var_labels = c(w = "Moderator"),
                    se = FALSE,
                    digits = 3)
ft2
Path:  x → m → y
[Moderator]
(Moderator)
Effect
Std. Effect
95% CI
M+1.0SD
3.164
3.060
0.318
[0.220
, 0.437]
Mean
2.179
2.136
0.222
[0.134
, 0.309]
M-1.0SD
1.194
1.212
0.126
[-0.031
, 0.260]
Note: [w] is the meaning of a level of moderator 'w'; (w) is the value of a level of moderator 'w': CI = confidence interval; Std. Effect is completely standardized effect.