Recreating APA Manual Table 7.16 in R with apa7

Making tables in APA style (Part 16 of 24)

In this 24-part series, each of the tables in Chapter 7 of the Publication Manual of the American Psychological Association (7th Edition) is recreated with apa7, flextable, easystats, and tidyverse functions.

NoteHighlights

• Two levels of grouping with flextable::as_grouped_data

library(apa7)
library(flextable)
library(ftExtra)
library(tidyverse)
set_flextable_defaults(theme_fun = theme_apa, 
                       font.family = "Times New Roman")

Figure 1

Screenshot of the APA Manual’s Table 7.16

Here I simulate and analyze path models of the actor-partner interdependence model. Getting the row titles to be centered under the t column took some trial-and-error.

```{r}
#| label: tbl-716
#| tbl-cap: "Regressions of Associations Between Marital 
#|           Satisfaction and Average Levels of Marital Behavior"
#| apa-note: "CI = confidence interval; H → H = husband-as-actor 
#|           effect on the husband’s own marital satisfaction; 
#|           W → W = wife-as-actor effect on the wife's own marital 
#|           satisfaction; W → H = wife-as-partner effect on the 
#|           husband’s satisfaction; H → W = husband-as-partner 
#|           effect on the wife's satisfaction."
set.seed(123)
# Make Coefficients
d_coefficients <- tibble::tribble(
        ~Dependent,    ~Group, ~Predictor,     ~b,
  "Angry Behavior",   "Actor",       "H_H",  -98.9,
  "Angry Behavior",   "Actor",       "W_W", -87.11,
  "Angry Behavior", "Partner",       "W_H", -76.18,
  "Angry Behavior", "Partner",       "H_W",  -91.8,
       "Disregard",   "Actor",       "H_H", -38.62,
       "Disregard",   "Actor",       "W_W", -47.54,
       "Disregard", "Partner",       "W_H", -82.81,
       "Disregard", "Partner",       "H_W", -79.36,
      "Distancing",   "Actor",       "H_H", -47.42,
      "Distancing",   "Actor",       "W_W",   3.04,
      "Distancing", "Partner",       "W_H",  -0.05,
      "Distancing", "Partner",       "H_W",  -53.5
  ) 

# Make Model
model <- d_coefficients |> 
  mutate(b = b / 100) |>
  unite(Predictor, c(Group, Predictor)) |> 
  mutate(across(c(Dependent, Predictor), snakecase::to_snake_case)) |> 
  unite(b, c(b, Predictor), sep = " * ") |> 
  summarise(b = paste(b, collapse = " + "), .by = Dependent) |> 
  unite(Model, c(Dependent, b), sep = " ~ ") |> 
  pull(Model) 

# Make data
d_simulated <- lavaan::simulateData(model, sample.nobs = 50) |> 
  as_tibble() |> 
  mutate(id = row_number(), .before = 0) |> 
  pivot_longer(angry_behavior:distancing, 
               values_to = "y", names_to = "Dependent") |> 
  mutate(y = y  * 100) |> 
  nest(data = -Dependent)


# Analyze data
d_analysis <- d_simulated |> 
  mutate(
    fit = map(data, \(d) {
      lm(y ~ ., data = d |> select(-id))
      }),
    tbl = map(fit, parameters::parameters))
  
# Format data
d_formatted <- d_analysis |> 
  select(Dependent, tbl) |> 
  unnest(tbl) |> 
  apa_format_columns() |> 
  filter(Variable != "Constant") |> 
  separate(Variable, c("Type", "i", "d")) |> 
  mutate(across(c(i,d), toupper)) |> 
  unite(Variable, c(i, d), sep = c(" \u2192 ")) |> 
  relocate(`95% CI`, .after = last_col()) |> 
  as_grouped_data(groups = c("Dependent", "Type")) |> 
  mutate(across(c(Type, Variable), \(x) tidyr::replace_na(x, ""))) |> 
  mutate(Variable = paste0(Type, Variable, recycle0 = TRUE),
         Dependent = snakecase::to_sentence_case(Dependent)) |> 
  fill(Dependent) |> 
  filter(Variable != "") |> 
  select(-Type)

# Make Table
d_formatted |> 
  apa_flextable(row_title_column = Dependent, 
                row_title_align = "center",
                line_spacing = 1.5, 
                no_format_columns = Variable) |> 
  padding(j = 1, 
          i = ~`*B*` != "", 
          padding.left = 20) |> 
  width(width = c(1.1, rep(.85, 4), 2)) 
```

Table 1

Regressions of Associations Between Marital Satisfaction and Average Levels of Marital Behavior

Variable	B	SE	t	p	95% CI
Angry behavior
Actor
H → H	−88.77	14.91	−5.96	<.001	[−118.79, −58.75]
W → W	−83.72	13.84	−6.05	<.001	[−111.60, −55.84]
Partner
W → H	−70.92	17.41	−4.07	<.001	[−105.98, −35.86]
H → W	−74.38	16.11	−4.62	<.001	[−106.83, −41.93]
Disregard
Actor
H → H	−33.51	14.08	−2.38	.02	[ −61.87,  −5.15]
W → W	−65.67	13.07	−5.02	<.001	[ −92.00, −39.34]
Partner
W → H	−78.89	16.44	−4.80	<.001	[−112.01, −45.77]
H → W	−83.30	15.22	−5.47	<.001	[−113.95, −52.65]
Distancing
Actor
H → H	−31.47	14.10	−2.23	.03	[ −59.86,  −3.08]
W → W	9.47	13.09	0.72	.47	[ −16.90,  35.83]
Partner
W → H	−14.79	16.47	−0.90	.37	[ −47.95,  18.37]
H → W	−73.34	15.24	−4.81	<.001	[−104.03, −42.65]

Note. CI = confidence interval; H → H = husband-as-actor effect on the husband’s own marital satisfaction; W → W = wife-as-actor effect on the wife’s own marital satisfaction; W → H = wife-as-partner effect on the husband’s satisfaction; H → W = husband-as-partner effect on the wife’s satisfaction.

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