<- read.csv("Data/R_data2.csv") dat
Markdown: Hints
Question 1
When using the template Rstudio this should not give any problems. Remember that the markdown code to start a section consists of two hashes ##
.
Question 2
To code chunk you should insert in the Setup section should look something like this:
Question 3
You can cary out all the transformationns using code like:
$pregnancy_length <- dat$pregnancy_length_weeks *7 +
dat$pregnancy_length_days
dat
$BMI_cat <- cut(dat$BMI, breaks=c(-Inf, 18.5, 24.9, 29.9, Inf),
datlabels=c("Underweight", "Healthy weight", "Overweight", "Obesity"))
$log_homocysteine <- log(dat$homocysteine)
dat
$log_vitaminB12 <- log(dat$vitaminB12)
dat
for(i in 1:length(names(dat))){
if(class(dat[[i]]) == "character"){
<- as.factor(dat[[i]])
dat[[i]]
}
}
$Status <- factor(dat$Status,
datlevels = c("normal brain development", "intellectual disability"))
<- dat[ , !(names(dat) %in% c("pregnancy_length_weeks", "pregnancy_length_days", "BMI", "homocysteine", "vitaminB12"))] dat
Question 4
To all the desciptives for all variables in the data set you can use the following code template:
for(i in 1:length(names(dat))){
if(class(dat[[i]]) == "numeric"){
# do something for numeric vriables
else if(class(dat[[i]]) == "factor"){
} # do something for factor variables
} }
Histograms can be created in a simular loop. To make the actual plot use the hist
function.
Question 5
Use the t.test
or wilcox.test
function to compare the mean of the logarithm of the Vitamin B12 for the two levels of Status
(normal brain development or intellectual disability).
Question 6
Use the glm
function to perform logistic regression analysis to investigate the association between Status
and log Vitamin B12
while adjusting for medication
, smoking
and alcohol
.
The code should look something like:
<- glm(formula, data = dat, family = binomial) glm1_adjusted
Use the summary
, coef
and confint
functions to extract the following details.
Question 7
State your conclusions from the adjusted and unadjusted analysis.