_02-01_iq.qmd

## General Cognitive Ability {#sec-iq}

{{< include _02-01_iq_text.qmd >}}

```{r}
#| label: setup-iq
#| include: false

# Filter by domain
domains <- c("General Cognitive Ability")

# Target phenotype
pheno <- "iq"

# Read the CSV file into a data frame
iq <- readr::read_csv("data/neurocog.csv")
```

```{r}
#| label: export-iq
#| include: false
#| eval: true

iq <- iq |>
  dplyr::filter(domain %in% domains)

# Select specific columns from the data frame
iq <- iq |>
  dplyr::select(
    test,
    test_name,
    scale,
    raw_score,
    score,
    ci_95,
    percentile,
    range,
    domain,
    subdomain,
    narrow,
    pass,
    verbal,
    timed,
    result,
    z,
    z_mean_domain,
    z_sd_domain,
    z_mean_subdomain,
    z_sd_subdomain,
    z_mean_narrow,
    z_sd_narrow,
    z_mean_pass,
    z_sd_pass,
    z_mean_verbal,
    z_sd_verbal,
    z_mean_timed,
    z_sd_timed
  )

# Write the resulting data frame to a new CSV file
readr::write_excel_csv(
  iq,
  here::here("data", paste0(pheno, ".csv")),
  na = "",
  col_names = TRUE,
  append = FALSE
)
```

```{r}
#| label: data-iq
#| include: false
#| eval: true

# Define the scales of interest
scales <- c(
  "Auditory Working Memory (AWMI)",
  "Cognitive Proficiency (CPI)",
  "Crystallized Knowledge",
  "Fluid Reasoning (FRI)",
  "Fluid Reasoning",
  "Full Scale (FSIQ)",
  "Full Scale IQ (FSIQ)",
  "General Ability (GAI)",
  "General Ability",
  "General Intelligence",
  "Global Neurocognitive Index (G)",
  "NAB Attention Index",
  "NAB Executive Functions Index",
  "NAB Language Index",
  "NAB Memory Index",
  "NAB Spatial Index",
  "NAB Total Index",
  "Nonverbal (NVI)",
  "Perceptual Reasoning (PRI)",
  "Perceptual Reasoning",
  "Processing Speed (PSI)",
  "Processing Speed",
  "RBANS Total Index",
  "Test of Premorbid Functioning",
  "TOPF Standard Score",
  "Total NAB Index (T-NAB)",
  "Verbal Comprehension (VCI)",
  "Verbal Comprehension",
  "Visual Perception/Construction",
  "Visual Spatial (VSI)",
  "Vocabulary Acquisition (VAI)",
  "Word Reading",
  "Working Memory (WMI)",
  "Working Memory",
  "Attention Index (ATT)",
  "Language Index (LAN)",
  "Spatial Index (SPT)",
  "Memory Index (MEM)",
  "Executive Functions Index (EXE)"
)

# Filter the data using the filter_data function from the bwu library
data_iq <- bwu::filter_data(data = iq, domain = domains, scale = scales)
```

```{r}
#| label: text-iq
#| cache: true
#| include: false

# export text
bwu::cat_neuropsych_results(data = data_iq, file = "_02-01_iq_text.qmd")
```

```{r}
#| label: qtbl-iq
#| dev: tikz
#| fig-process: pdf2png
#| include: false
#| eval: true

# Set the default engine for tikz to "xetex"
options(tikzDefaultEngine = "xetex")

# Define the scales to include
subset <- c(
  "Auditory Working Memory (AWMI)",
  "Cognitive Proficiency (CPI)",
  "Crystallized Knowledge",
  "Fluid Reasoning (FRI)",
  "Fluid Reasoning",
  "Full Scale (FSIQ)",
  "Full Scale IQ (FSIQ)",
  "General Ability (GAI)",
  "General Ability",
  "General Intelligence",
  "Global Neurocognitive Index (G)",
  "NAB Attention Index",
  "NAB Executive Functions Index",
  "NAB Language Index",
  "NAB Memory Index",
  "NAB Spatial Index",
  "NAB Total Index",
  "Nonverbal (NVI)",
  "Perceptual Reasoning (PRI)",
  "Perceptual Reasoning",
  "Processing Speed (PSI)",
  "Processing Speed",
  "RBANS Total Index",
  "Test of Premorbid Functioning",
  "TOPF Standard Score",
  "Total NAB Index (T-NAB)",
  "Verbal Comprehension (VCI)",
  "Verbal Comprehension",
  "Visual Perception/Construction",
  "Visual Spatial (VSI)",
  "Vocabulary Acquisition (VAI)",
  "Word Reading",
  "Working Memory (WMI)",
  "Working Memory",
  "Attention Index (ATT)",
  "Language Index (LAN)",
  "Spatial Index (SPT)",
  "Memory Index (MEM)",
  "Executive Functions Index (EXE)"
)

# Filter the data to subset only the specified scales
data_iq <- dplyr::filter(data_iq, scale %in% subset)

# Define the table name, vertical padding, and multiline setting
pheno <- "iq"
table_name <- "table_iq"
vertical_padding <- 0
multiline <- TRUE

# footnotes
fn_standard_score <- gt::md(
  "Standard score: Mean = 100 [50th‰], SD ± 15 [16th‰, 84th‰]"
)

source_note <- gt::md(
  "Standard score: Mean = 100 [50th‰], SD ± 15 [16th‰, 84th‰]"
)

# Define the groups for the table
grp_iq <- list(
  standard_score = c(
    "Composite Scores",
    "Test of Premorbid Functioning",
    "WAIS-5",
    "WAIS-IV",
    "WAIS-4",
    "WASI-2",
    "WISC-5",
    "WISC-V",
    "WRAT-5",
    "KTEA-3",
    "NAB",
    "NAB-S",
    "RBANS",
    "WPPSI-IV"
  )
)

# Create the table using the NeurotypR::tbl_gt2 function from the bwu library
NeurotypR::tbl_gt(
  data = data_iq,
  pheno = pheno,
  table_name = table_name,
  vertical_padding = vertical_padding,
  source_note = source_note,
  # fn_standard_score = fn_standard_score,
  # grp_standard_score = grp_iq[["standard_score"]],
  dynamic_grp = grp_iq,
  multiline = multiline
)
```

```{r}
#| label: fig-iq-subdomain
#| include: false
#| eval: true
#| fig-cap: "_Premorbid Ability_ is an estimate of an individual's intellectual functioning prior to known or suspected onset of brain disease or dysfunction. _General Ability_ is the overall skill to reason, solve problems, and gain useful knowledge. _Crystallized Knowledge_ involves understanding the world through language and reasoning. _Fluid Reasoning_ is the logical analysis and solution of new problems, identifying underlying patterns, and applying logic."

# Define the x and y variables for the dotplot (as column names)
x <- data_iq$z_mean_subdomain
y <- data_iq$subdomain

# plot args
colors <- NULL
return_plot <- TRUE
filename <- "fig_iq_subdomain.svg"

# Define the scales to keep
# keep <- c("General Ability", "Crystallized Knowledge", "Fluid Reasoning")
# data_iq <- dplyr::filter(data_iq, scale %in% keep)
# source("R/dotplot2_efficient.R")
# Create the dotplot using the dotplot function from the bwu library
NeurotypR::dotplot2(
  data = data_iq,
  x = x,
  y = y,
  colors = colors,
  return_plot = return_plot,
  filename = filename,
  na.rm = TRUE
)
```

```{r}
#| label: fig-iq-narrow
#| include: false
#| fig-cap: "_Premorbid Ability_ is an estimate of an individual's intellectual functioning prior to known or suspected onset of brain disease or dysfunction. _General Ability_ is the overall skill to reason, solve problems, and gain useful knowledge. _Crystallized Knowledge_ involves understanding the world through language and reasoning. _Fluid Reasoning_ is the logical analysis and solution of new problems, identifying underlying patterns, and applying logic."

# Define the x and y variables for the dotplot (as column names)
x <- data_iq$z_mean_narrow
y <- data_iq$narrow

# plot args
colors <- NULL
return_plot <- TRUE

# Define the filename for the plot
filename <- "fig_iq_narrow.svg"

# Define the scales to keep
# keep <- c("General Ability", "Crystallized Knowledge", "Fluid Reasoning")
# data_iq <- dplyr::filter(data_iq, scale %in% keep)

# Create the dotplot using the dotplot function from the NeurotypR package
NeurotypR::dotplot2(
  data = data_iq,
  x = x,
  y = y,
  colors = colors,
  return_plot = return_plot,
  filename = filename,
  na.rm = TRUE
)
```

```{=typst}
// Define a function to create a domain with a title, a table, and a figure
#let domain(title: none, file_qtbl, file_fig) = {
  let font = (font: "Roboto Slab", size: 0.7em)
  set text(..font)
  pad(top: 0.5em)[]
  grid(
    columns: (50%, 50%),
    gutter: 8pt,
    figure(
      [#image(file_qtbl)],
      caption: figure.caption(position: top, [#title]),
      kind: "qtbl",
      supplement: [*Table*],
    ),
    figure(
      [#image(file_fig, width: auto)],
      caption: figure.caption(
        position: bottom,
        [#emph[_Premorbid Ability_] is an estimate of an individual's intellectual functioning prior to known or suspected onset of brain disease or dysfunction. Neurocognition is independent of intelligence and evaluates cognitive functioning across five domains\: Attention (focus, concentration, and information processing), Language (verbal communication, naming, comprehension, and fluency), Memory (immediate and delayed verbal and visual recall), Spatial (visuospatial perception, construction, and orientation), and Executive Functions (planning, problem-solving, and mental flexibility). #footnote[All scores in these figures have been standardized as z-scores. In this system: A z-score of 0.0 represents average performance; Each unit represents one standard deviation from the average; Scores between -1.0 and +1.0 fall within the normal range; Scores below -1.0 indicate below-average performance and warrant attention; and Scores at or below -2.0 indicate significantly impaired performance and are clinically concerning.]
        ],
      ),
      placement: none,
      kind: "image",
      supplement: [*Figure*],
      gap: 0.5em,
    ),
  )
}
```

```{=typst}
// Define the title of the domain
#let title = "General Cognitive Ability"

// Define the file name of the table
#let file_qtbl = "table_iq.png"

// Define the file name of the figure
#let file_fig = "fig_iq_subdomain.svg"

// The title is appended with ' Index Scores'
#domain(title: [#title Scores], file_qtbl, file_fig)
```

<!-- ```{=typst}
// Define the title of the domain
#let title = "General Cognitive Ability"

// Define the file name of the table
#let file_qtbl = "table_iq.png"

// Define the file name of the figure
#let file_fig = "fig_iq_narrow.svg"

// The title is appended with ' Index Scores'
#domain(title: [#title Scores], file_qtbl, file_fig)
``` -->