Carcinoma {ggpcp}

Data set: Assessment of Carcinoma slides

Description

A differently formatted data is set available as carcinoma in package poLCA. Here, pathologists' ratings are recorded

Usage

Carcinoma

Format

A data frame with 118 rows and 9 variables:

Overall structure

No

slide number 1 through 126 (data for slides 14, 20, 21, 50, 75, 97, 109, and 125 are missing)

Average

average rating of all eight pathologists.

Pathologist ratings

A

scores 1 to 5 of pathologist's A evaluation (1) Negative; (2) Atypical Squamous Hyperplasia; (3) Carcinoma in Situ; (4) Squamous Carcinoma with Early Stromal Invasion; (5) Invasive Carcinoma.

B

scores by pathologist B.

C

scores by pathologist C.

D

scores by pathologist D.

E

scores by pathologist E.

F

scores by pathologist F.

G

scores by pathologist G.

Source

Data published as Table 1 in Landis, J. Richard, and Koch, Gary G. "An Application of Hierarchical Kappa-type Statistics in the Assessment of Majority Agreement among Multiple Observers." Biometrics 33.2 (1977): 363-74, doi:10.2307/2529786.

Study and Design in Holmquist, Nelson D., McMahan C.A., Williams O. Dale. Variability in classification of carcinoma in situ of the uterine cervix. Arch Pathol. 1967 Oct;84(4):334-45. PMID: 6045443, doi:10.1097/00006254-196806000-00023.

Examples

library(ggplot2)
Carcinoma |>
  pcp_select(F, D, C, A, G, E, B, Average) |>
  pcp_scale(method="uniminmax") |>
  pcp_arrange() |>
  ggplot(aes_pcp()) +
    geom_pcp_axes() +
    geom_pcp(aes(colour = Average > 2)) +
    geom_pcp_boxes(colour="black", alpha=0) +
    geom_pcp_labels(aes(label = pcp_level), fill="white", alpha = 1) +
    theme_bw() +
    scale_x_discrete(expand = expansion(add=0.25)) +
    xlab("Pathologist") + ylab("Carcinoma score 1 (Negative) to 5 (Invasive Carcinoma)") +
    theme(axis.text.y=element_blank(), axis.ticks.y=element_blank(), legend.position="none")