Hearing Loss in Children

1 Setting up R Packages

Plot Fonts and Theme

Show the Code
library(systemfonts)
library(showtext)
## Clean the slate
systemfonts::clear_local_fonts()
systemfonts::clear_registry()
##
showtext_opts(dpi = 96) # set DPI for showtext
sysfonts::font_add(
  family = "Alegreya",
  regular = "../../../../../../fonts/Alegreya-Regular.ttf",
  bold = "../../../../../../fonts/Alegreya-Bold.ttf",
  italic = "../../../../../../fonts/Alegreya-Italic.ttf",
  bolditalic = "../../../../../../fonts/Alegreya-BoldItalic.ttf"
)

sysfonts::font_add(
  family = "Roboto Condensed",
  regular = "../../../../../../fonts/RobotoCondensed-Regular.ttf",
  bold = "../../../../../../fonts/RobotoCondensed-Bold.ttf",
  italic = "../../../../../../fonts/RobotoCondensed-Italic.ttf",
  bolditalic = "../../../../../../fonts/RobotoCondensed-BoldItalic.ttf"
)
showtext_auto(enable = TRUE) # enable showtext
##
theme_custom <- function() {
  font <- "Alegreya" # assign font family up front
  "%+replace%" <- ggplot2::"%+replace%" # nolint

  theme_classic(base_size = 14, base_family = font) %+replace% # replace elements we want to change

    theme(
      text = element_text(family = font), # set base font family

      # text elements
      plot.title = element_text( # title
        family = font, # set font family
        size = 24, # set font size
        face = "bold", # bold typeface
        hjust = 0, # left align
        margin = margin(t = 5, r = 0, b = 5, l = 0)
      ), # margin
      plot.title.position = "plot",
      plot.subtitle = element_text( # subtitle
        family = font, # font family
        size = 14, # font size
        hjust = 0, # left align
        margin = margin(t = 5, r = 0, b = 10, l = 0)
      ), # margin

      plot.caption = element_text( # caption
        family = font, # font family
        size = 9, # font size
        hjust = 1
      ), # right align

      plot.caption.position = "plot", # right align

      axis.title = element_text( # axis titles
        family = "Roboto Condensed", # font family
        size = 12
      ), # font size

      axis.text = element_text( # axis text
        family = "Roboto Condensed", # font family
        size = 9
      ), # font size

      axis.text.x = element_text( # margin for axis text
        margin = margin(5, b = 10)
      )

      # since the legend often requires manual tweaking
      # based on plot content, don't define it here
    )
}

## Use available fonts in ggplot text geoms too!
ggplot2::update_geom_defaults(geom = "text", new = list(
  family = "Roboto Condensed",
  face = "plain",
  size = 3.5,
  color = "#2b2b2b"
))
ggplot2::update_geom_defaults(geom = "label", new = list(
  family = "Roboto Condensed",
  face = "plain",
  size = 3.5,
  color = "#2b2b2b"
))

## Set the theme
ggplot2::theme_set(new = theme_custom())

2 Introduction

Children are monitored for OME (Otitis Media with Effusion, i.e. fluid in the middle ear) over time. It is believed that they later ( i.e. during aduldhood) suffer from “binaural hearing loss” (detecting sound amplitude and direction) after past episodes of OME during their childhood. The hearing-test is conducted multiple times, with a Test Signal embedded in noise played over audio loudspeakers. One loudspeaker has only Noise, and the other loudspeaker has the Test Signal in Noise. There are also two types of Test Signals: one is like noise itself and the other is distinct. In any test round, children are expected to orient themselves towards the appropriate loudspeaker and detect the presence of the Test Signal at varying levels of volume, with a passing success rate of 75% over multiple tests.

This dataset is available on Vincent Arel-Bundock’s dataset repository and is a part of the R package MASS.

3 Read the Data

ome <- read_csv("https://vincentarelbundock.github.io/Rdatasets/csv/MASS/OME.csv")
glimpse(ome)
Rows: 1,097
Columns: 8
$ rownames <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18…
$ ID       <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3…
$ Age      <dbl> 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 60, 60, 60, 60, 60, 6…
$ OME      <chr> "low", "low", "low", "low", "low", "low", "low", "low", "low"…
$ Loud     <dbl> 35, 35, 40, 40, 45, 45, 50, 50, 55, 55, 35, 35, 40, 40, 45, 4…
$ Noise    <chr> "coherent", "incoherent", "coherent", "incoherent", "coherent…
$ Correct  <dbl> 1, 4, 0, 1, 2, 2, 3, 4, 3, 2, 2, 3, 1, 1, 1, 5, 4, 2, 3, 4, 4…
$ Trials   <dbl> 4, 5, 3, 1, 4, 2, 3, 4, 3, 2, 4, 4, 4, 1, 2, 5, 4, 2, 3, 4, 6…
ome

4 Data Dictionary

NoteQuantitative Variables

Write in.

NoteQualitative Variables

Write in.

NoteObservations

Write in.

5 Research Question

Note

In hearing tests on people with varying levels of OME infection in their childhood, what is the effect of using distinct types of Test Signal on successful (face) orientation ?

6 Analyse/Transform the Data

```{r}
#| label: data-preprocessing
#
# Write in your code here
# to prepare this data as shown below
# to generate the plot that follows
# Rename Variables if needed
# Change data to factors etc.
# Set up Counts, histograms etc
```

7 Plot the Data

Error in `position_dodge()`:
! `orientation` must be a string or character vector.

8 Task and Discussion

  • Complete the Data Dictionary.
  • Select and Transform the variables as shown.
  • Create the graphs shown and discuss the following questions:
    • Identify the type of charts
    • Identify the variables used for various geometrical aspects (x, y, fill…). Name the variables appropriately.
    • What research activity might have been carried out to obtain the data graphed here? Provide some details.
    • What pre-processing of the data was required to create the chart?
    • Write a 2-line story based on the chart, describing your inference/surprise. Is there something counter-intuitive (to a lay person) in the chart?
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