1 Description

The body fat was measured, using dual-energy x-ray absorptiometry, in several hundred children at age 11, 13, and 15 years.

Use the data set (in Stata dta format) to answer the following questions:
(a) Does body fat increase with age for both girls and boys?
(b) Is there a difference between girls and boys with respect to the increase of the body fat with age?
(c) Do girls tend to have more body fat than boys?

Source: Vach, W. (2013). Regression Models as a Tool in Medical Research. p. 330. Chapman/Hall & CRC Press.

Column 1: Subject ID
Column 2: Gender ID
Column 3: Age in years
Column 4: Body fat in kilograms

2 Input Data

pacman::p_load(foreign)
dta3 <- read.dta("C:/Users/HANK/Desktop/HOMEWORK/bodyfat.dta", 
                 convert.dates = TRUE,
                 convert.factors = TRUE,
                 missing.type = FALSE,
                 convert.underscore = FALSE,
                 warn.missing.labels = TRUE)
str(dta3)
## 'data.frame':    2273 obs. of  4 variables:
##  $ id     : num  1 1 1 2 2 2 3 3 3 4 ...
##  $ sex    : Factor w/ 2 levels "female","male": 2 2 2 1 1 1 1 1 1 1 ...
##  $ age    : num  11 13 15 11 13 15 11 13 15 11 ...
##  $ bodyfat: num  4 6.2 10.5 8.1 10.4 ...
##  - attr(*, "datalabel")= chr ""
##  - attr(*, "time.stamp")= chr "21 May 2011 13:30"
##  - attr(*, "formats")= chr [1:4] "%9.0g" "%9.0g" "%9.0g" "%9.0g"
##  - attr(*, "types")= int [1:4] 254 254 254 254
##  - attr(*, "val.labels")= chr [1:4] "" "labsex" "" ""
##  - attr(*, "var.labels")= chr [1:4] "group(u)" "" "" ""
##  - attr(*, "version")= int 8
##  - attr(*, "label.table")=List of 1
##   ..$ labsex: Named int [1:2] 1 2
##   .. ..- attr(*, "names")= chr [1:2] "female" "male"
head(dta3)
##   id    sex age bodyfat
## 1  1   male  11     4.0
## 2  1   male  13     6.2
## 3  1   male  15    10.5
## 4  2 female  11     8.1
## 5  2 female  13    10.4
## 6  2 female  15    15.2

3 plot

ggplot(dta3, aes(age, bodyfat,
                  group = id,
                  color = id)) +
  geom_point()+
  stat_summary(fun = mean, geom = "line") +
  #stat_summary(fun = mean, geom = "point") +
  #stat_summary(fun.data = mean_se, geom = "errorbar", width = 0.3) +
  #scale_shape_manual(values = c(1, 2)) +
  facet_wrap( ~ sex)+
  labs(x = "Age (in years)", 
       y = "Body fat (in %)") +
  theme(legend.justification = c(1, 1), 
        legend.position = c(1, 1),
        legend.background = element_rect(fill = "white",color = "black"))