Identitying Complete Cases

Often we wish to exclude subjects from some or all of

our analysis if they have any missing values. Otherwise,

comparing measurements across timepoints could be

confounded by differences in group members.

To make a dataframe with only complete cases across

all variables we can again use the filter command on the

card dataframe, and this time we will pass in

"complete.cases$($card$)"$ as an argument". This argument

will, as the name implies, return "TRUE" only for those

rows that have no missing values for any variable. Any

row with even a single missing value will return "FALSE"

and thus be eliminated by the filter command.

Use filter and the complete.cases$($card$)$ argument to

create a dataframe called "card$\_$cpt$".$ Analyze this

dataframe and answer the question below.

Number of females with no missing values $=$