2 Intro: Cancer Experiemnt

library(tidyverse)       # super helpful everything!
library(haven)           # inporting SPSS, SAS, & Stata data files
library(psych)           # lots of nice tidbits

2.1 Source of Data

Mid-Michigan Medical Center, Midland, Michigan, 1999: A study of oral condition of cancer patients.

2.2 Description of the Study

The data set contains part of the data for a study of oral condition of cancer patients conducted at the Mid-Michigan Medical Center. The oral conditions of the patients were measured and recorded at the initial stage, at the end of the second week, at the end of the fourth week, and at the end of the sixth week. The variables age, initial weight and initial cancer stage of the patients were recorded. Patients were divided into two groups at random: One group received a placebo and the other group received aloe juice treatment.

Sample size n = 25 patients with neck cancer.

The treatment is Aloe Juice.

2.3 Variables

  • ID patient identification number

  • trt treatment group

    • 0 placebo
    • 1 aloe juice

  • age patient’s age, in years

  • weightin patient’s weight (pounds) at the initial stage

  • stage initial cancer stage

    • coded 1 through 4

  • totalcin oral condition at the initial stage

  • totalcw2 oral condition at the end of week 2

  • totalcw4 oral condition at the end of week 4

  • totalcw6 oral condition at the end of week 6

2.4 Import Data

The Cancer dataset is saved in SPSS format, which is evident from the .sav ending on the file name.

The haven package is downloaded as part of the tidyverse set of packages, but is not automatically loaded. It must have its own library() function call (see above). The haven::read_spss() function works very simarly to the readxl::read_excel() function we used last chapter (Wickham, Miller, and Smith 2022).

  • Make sure the dataset is saved in the same folder as this file
  • Make sure the that folder is the working directory
cancer_raw <- haven::read_spss("https://github.com/CEHS-research/PSY-6600_students/raw/master/Data/Cancer.sav")
tibble::glimpse(cancer_raw)
Rows: 25
Columns: 9
$ ID       <dbl> 1, 5, 6, 9, 11, 15, 21, 26, 31, 35, 39, 41, 45, 2, 12, 14, 16…
$ TRT      <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1…
$ AGE      <dbl> 52, 77, 60, 61, 59, 69, 67, 56, 61, 51, 46, 65, 67, 46, 56, 4…
$ WEIGHIN  <dbl> 124.0, 160.0, 136.5, 179.6, 175.8, 167.6, 186.0, 158.0, 212.8…
$ STAGE    <dbl> 2, 1, 4, 1, 2, 1, 1, 3, 1, 1, 4, 1, 1, 2, 4, 1, 2, 1, 4, 2, 1…
$ TOTALCIN <dbl> 6, 9, 7, 6, 6, 6, 6, 6, 6, 6, 7, 6, 8, 7, 6, 4, 6, 6, 12, 5, …
$ TOTALCW2 <dbl> 6, 6, 9, 7, 7, 6, 11, 11, 9, 4, 8, 6, 8, 16, 10, 6, 11, 7, 11…
$ TOTALCW4 <dbl> 6, 10, 17, 9, 16, 6, 11, 15, 6, 8, 11, 9, 9, 9, 11, 8, 11, 6,…
$ TOTALCW6 <dbl> 7, 9, 19, 3, 13, 11, 10, 15, 8, 7, 11, 6, 10, 10, 9, 7, 14, 6…

2.5 Wrangle Data

cancer_clean <- cancer_raw %>% 
  dplyr::rename_all(tolower) %>% 
  dplyr::mutate(id = factor(id)) %>% 
  dplyr::mutate(trt = factor(trt,
                             labels = c("Placebo", 
                                        "Aloe Juice"))) %>% 
  dplyr::mutate(stage = factor(stage))

2.6 Overview

2.6.1 Dimentions (size) of the dataset

dim(cancer_clean)
[1] 25  9

2.6.2 Variable Names

names(cancer_clean)
[1] "id"       "trt"      "age"      "weighin"  "stage"    "totalcin" "totalcw2"
[8] "totalcw4" "totalcw6"

2.6.3 Quick Glimpse

tibble::glimpse(cancer_clean)
Rows: 25
Columns: 9
$ id       <fct> 1, 5, 6, 9, 11, 15, 21, 26, 31, 35, 39, 41, 45, 2, 12, 14, 16…
$ trt      <fct> Placebo, Placebo, Placebo, Placebo, Placebo, Placebo, Placebo…
$ age      <dbl> 52, 77, 60, 61, 59, 69, 67, 56, 61, 51, 46, 65, 67, 46, 56, 4…
$ weighin  <dbl> 124.0, 160.0, 136.5, 179.6, 175.8, 167.6, 186.0, 158.0, 212.8…
$ stage    <fct> 2, 1, 4, 1, 2, 1, 1, 3, 1, 1, 4, 1, 1, 2, 4, 1, 2, 1, 4, 2, 1…
$ totalcin <dbl> 6, 9, 7, 6, 6, 6, 6, 6, 6, 6, 7, 6, 8, 7, 6, 4, 6, 6, 12, 5, …
$ totalcw2 <dbl> 6, 6, 9, 7, 7, 6, 11, 11, 9, 4, 8, 6, 8, 16, 10, 6, 11, 7, 11…
$ totalcw4 <dbl> 6, 10, 17, 9, 16, 6, 11, 15, 6, 8, 11, 9, 9, 9, 11, 8, 11, 6,…
$ totalcw6 <dbl> 7, 9, 19, 3, 13, 11, 10, 15, 8, 7, 11, 6, 10, 10, 9, 7, 14, 6…

2.6.4 Top and Bottom Rows

psych::headTail(cancer_clean)
    id        trt age weighin stage totalcin totalcw2 totalcw4 totalcw6
1    1    Placebo  52     124     2        6        6        6        7
2    5    Placebo  77     160     1        9        6       10        9
3    6    Placebo  60   136.5     4        7        9       17       19
4    9    Placebo  61   179.6     1        6        7        9        3
5 <NA>       <NA> ...     ...  <NA>      ...      ...      ...      ...
6   42 Aloe Juice  73   181.5     0        8       11       16     <NA>
7   44 Aloe Juice  67     187     1        5        7        7        7
8   50 Aloe Juice  60     164     2        6        8       16     <NA>
9   58 Aloe Juice  54   172.8     4        7        8       10        8