# [Rd] For wishlist: sanity checks for subsets in lm, glm (PR#515)

**plummer@iarc.fr
**
plummer@iarc.fr

*Wed, 12 Apr 2000 11:55:37 +0200 (MET DST)*

I got stung by this yesterday:
R> x <- seq(0,1,length=101)
R> y <- x + rnorm(101)/5
R> test.data <- data.frame(x=x, y=y, cond=(x <= 0.5))
R> # A perfect fit! But very implausible parameter estimates.
R> glm(y ~ x, data=test.data, subset=cond)
Call: glm(formula = y ~ x, data = test.data, subset = cond)
Coefficients:
(Intercept) x
-0.1283 29.5571
Degrees of Freedom: 100 Total (i.e. Null); 99 Residual
Null Deviance: 2.206
Residual Deviance: 3.929e-32 AIC: -7477
R> # Here's why ...
R> test.data2 <- test.data[test.data$cond, ]
R> table(test.data2$x, test.data2$y)
-0.128278372512167 0.167292488167292
0 50 0
0.01 0 51
R> # ... I just replicated the first two rows
R> test.data[1:2,]
x y cond
1 0.00 -0.1282784 TRUE
2 0.01 0.1672925 TRUE
Now, I admit that this isn't a bug. I should have used
R> test.data <- data.frame(x=x, y=y, cond=I(x <= 0.5))
to preserve cond as a logical vector, as documented in the help for
data.frame. However, it is still very unpleasant behaviour, and no
warnings were issued. I can't help thinking that some sanity checks on
the subset argument could have helped me.
So I suggest that the subset argument should either be
* A logical vector of the same length as the number of rows in the data
frame, or
* A numeric vector of unique integers
to ensure that we really do get a subset of the data frame. The more
flexible behaviour of "[.data.frame" really isn't required here.
Martyn
--please do not edit the information below--
Version:
platform = i686-unknown-linux
arch = i686
os = linux
system = i686, linux
status =
major = 1
minor = 0.0
year = 2000
month = February
day = 29
language = R
Search Path:
.GlobalEnv, Autoloads, package:base
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