Using an abbreviated version of the 2015 UK Millennium Cohort survey dataset (mcs.dta), perform the following exercises. Note: the survey was carried out in 2015 to 14 year-old pupil in the UK. The dataset consists of nearly 12,000 observations and 52 variables. You need to use the haven package to read-in the data. Perform recoding and labeling on the variables below. Note: for all the variables, you need to first convert them to factors using the as.factor() function.
mths - rename as maths and label the values as 1=’1. Strongly Disagree’;2=’2. Disagree’;3=’3. Agree’;4=’4. Strongly Agree’. This variable includes pupils’ responses to whether they were good at mathematics.
Read-in 2015 Millennium Cohort Study data.
setwd("c:/QSSD/Exercises/Chapter 5 - Exercises")
getwd()
[1] "c:/QSSD/Exercises/Chapter 5 - Exercises"
library(haven)
mcs <- read_dta("mcs.dta")
library(car)
Warning: package 'car' was built under R version 3.4.3
mcs$mths <- as.factor(mcs$mths)
table(mcs$mths)
1 2 3 4
598 1827 5958 3118
mcs$maths <- recode(mcs$mths, "1='1. Strongly Disagree';2='2. Disagree';
3='3. Agree';4='4. Strongly Agree'")
table(mcs$maths)
1. Strongly Disagree 2. Disagree 3. Agree
598 1827 5958
4. Strongly Agree
3118
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