Chain subset conditions
Chain subset conditions
chainsubset(..., out.vars)
... |
Logical conditions to be chained. |
out.vars |
character. Variables not in data.frame, only needed if you use variables which
are not in the frame. If |
A set of logical conditions are chained, not and'ed. That is, each argument to
chainsubset is used as a filter to create a smaller dataset. Each subsequent
argument filters further.
For independent conditions this will be the same as and'ing them. I.e.
chainsubset(x < 0 , y < 0) will yield the same subset as (x < 0) & (y < 0).
However, for aggregate filters like chainsubset(x < mean(y), x > mean(y))
we first find all the observations with x < mean(y), then among these we
find the ones with x > mean(y). The last mean(y) is now conditional on
x < mean(y).
Expression that can be eval'ed to yield a logical subset mask.
Some trickery is done to make this work directly in the subset argument of functions like
felm() and lm(). It might possibly fail with an error message in some situations.
If this happens, it should be done in two steps: ss <- eval(chainsubset(...),data);
lm(...,data=data, subset=ss). In particular, the arguments are taken literally,
constructions like function(...) {chainsubset(...)} or a <- quote(x < y); chainsubset(a) do
not work, but do.call(chainsubset,list(a)) does.
set.seed(48) N <- 10000 dat <- data.frame(y=rnorm(N), x=rnorm(N)) # It's not the same as and'ing the conditions: felm(y ~ x,data=dat,subset=chainsubset(x < mean(y), y < 2*mean(x))) felm(y ~ x,data=dat,subset=chainsubset(y < 2*mean(x), x < mean(y))) felm(y ~ x,data=dat,subset=(x < mean(y)) & (y < 2*mean(x))) lm(y ~ x, data=dat, subset=chainsubset(x < mean(y), x > mean(y)))
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