Children served in EI: National and Oregon Data

This is the first step in my visualization series. I created a simple kable table using data from the Office of Special Education Programs (OSEP).

To give some background, my dissertation will focus on equitable access to Early Intervention (EI) for different groups. Some of the visualizations in this blog will be adjusted to allow for stronger statistical analysis, such as by incorporating census data.

Here’s what my dataset looked like after I finished wrangling the data:

print(race_us_chart)

# A tibble: 7 × 7
  Race                  Disqualified `Moved Out` `Not Determined` `Not Eligible`
  <chr>                        <dbl>       <dbl>            <dbl>          <dbl>
1 Alaska Native or Ame…         3262        1045             2480           4395
2 Asian                         6559        8031            22848          26712
3 Black or African Ame…        56155       14648            69687          65353
4 Hispanic or Latino           79951       26699           173416         165654
5 Two or More Races            11676        6477            15813          28996
6 Pacific Islander               977         559             1532           1911
7 White                        99922       65399           178843         402568
# ℹ 2 more variables: `Part B Eligible` <dbl>, Withdrawn <dbl>

This may look simple, but just a few months ago, I was completely new to R, RStudio, and GitHub. I used many functions for data wrangling, including filter(), select(), mutate(), bind_rows(), mutate(), group_by(), pivot_longer(), pivot_wider(), and summarize().

kable(race_us_chart, 
      caption = "Exit Reasons and Race (National)", 
      align = "c") %>%  
  kable_styling(
    full_width = F, 
    position = "center",  
    bootstrap_options = c("striped", "hover")) %>%   
  row_spec(0, align = "c")

Exit Reasons and Race (National)
Race	Disqualified	Moved Out	Not Determined	Not Eligible	Part B Eligible	Withdrawn
Alaska Native or American Indian	3262	1045	2480	4395	9035	3155
Asian	6559	8031	22848	26712	52840	21737
Black or African American	56155	14648	69687	65353	139607	48699
Hispanic or Latino	79951	26699	173416	165654	318999	109469
Two or More Races	11676	6477	15813	28996	50699	19195
Pacific Islander	977	559	1532	1911	3587	1467
White	99922	65399	178843	402568	623690	242489

I will build on this simple table to start analyzing the data more deeply. But first, I will show how disparities appear across the United States, where racially marginalized children are often under-served in EI, unlike in K-12 special education.