r - model.matrix() with na.action=NULL?

Question

I have a formula and a data frame, and I want to extract the model.matrix(). However, I need the resulting matrix to include the NAs that were found in the original dataset. If I were to use model.frame() to do this, I would simply pass it na.action=NULL. However, the output I need is of the model.matrix() format. Specifically, I need only the right-hand side variables, I need the output to be a matrix (not a data frame), and I need factors to be converted to a series of dummy variables.

I'm sure I could hack something together using loops or something, but I was wondering if anyone could suggest a cleaner and more efficient workaround. Thanks a lot for your time!

And here's an example:

dat <- data.frame(matrix(rnorm(20),5,4), gl(5,2))
dat[3,5] <- NA
names(dat) <- c(letters[1:4], 'fact')
ff <- a ~ b + fact

# This omits the row with a missing observation on the factor
model.matrix(ff, dat) 

# This keeps the NA, but it gives me a data frame and does not dichotomize the factor
model.frame(ff, dat, na.action=NULL) 

Here is what I would like to obtain:

   (Intercept)          b fact2 fact3 fact4 fact5
1            1  0.7266086     0     0     0     0
2            1 -0.6088697     0     0     0     0
3            NA 0.4643360     NA    NA    NA    NA
4            1 -1.1666248     1     0     0     0
5            1 -0.7577394     0     1     0     0
6            1  0.7266086     0     1     0     0
7            1 -0.6088697     0     0     1     0
8            1  0.4643360     0     0     1     0
9            1 -1.1666248     0     0     0     1
10           1 -0.7577394     0     0     0     1

question from:https://stackoverflow.com/questions/5616210/model-matrix-with-na-action-null

Answer 1

Joris's suggestion works, but a quicker and cleaner way to do this is via the global na.action setting. The 'Pass' option achieves our goal of preserving NA's from the original dataset.

Option 1: Pass

Resulting matrix will contain NA's in rows corresponding to the original dataset.

options(na.action='na.pass')
model.matrix(ff, dat) 

Option 2: Omit

Resulting matrix will skip rows containing NA's.

options(na.action='na.omit')
model.matrix(ff, dat) 

Option 3: Fail

An error will occur if the original data contains NA's.

options(na.action='na.fail')
model.matrix(ff, dat) 

Of course, always be careful when changing global options because they can alter behavior of other parts of your code. A cautious person might store the original setting with something like current.na.action <- options('na.action'), and then change it back after making the model.matrix.