R help - May 2012 - warning with glm.predict, wrong number of data rows

Hi,
I split a data set into two partitions (80 and 42), use the first as the
training set in glm and the second as testing set in glm predict. But when I
call glm.predict, I get the warning message: 

Warning message:
'newdata' had 42 rows but variable(s) found have 80 rows 
---------------------
 s = sample(1:122)
glm.my.data=glm(my.data.class[s[1:80]]~t(my.data)[s[1:80],1:60],family="binomial")
pred.my.data =
predict(glm.gse13355,as.data.frame(t(my.data)[s[81:122],1:60]),type="response")
Warning message:
'newdata' had 42 rows but variable(s) found have 80 rows 

length(pred.my.data)
[1] 80

Thanks

Carol
	[[alternative HTML version deleted]]

carol white <wht_crl <at> yahoo.com> writes:
> 
> Hi,
> I split a data set into two partitions (80 and 42), use the first as the
training set in glm and the second as
> testing set in glm predict. But when I call glm.predict, I get the warning
message:?
> 
> Warning message:
> 'newdata' had 42 rows but variable(s) found have 80 rows?
> ---------------------
[snip]

The warning correctly diagnoses the problem.

The posting guide asks for a 'reproducible example', but you did not
give us one.

There is one below. 

Note what happens when predict() tries to reconstruct the variable
'x[1:4]'
as dictated by the formula.

How many elements can 'x[1:4]' have when newdata has (say) nrowsNew?

Use the subset argument to select a subset of observations.

> y <- sample(factor(1:2),80,repl=T)
> y <- sample(factor(1:2),5,repl=T)
> x <- 1:4
> fit <- glm( y[1:4] ~ x[1:4], family = binomial)
> fit
Call:  glm(formula = y[1:4] ~ x[1:4], family = binomial)

Coefficients:
(Intercept)       x[1:4]  
 -1.110e-16    0.000e+00  

Degrees of Freedom: 3 Total (i.e. Null);  2 Residual
Null Deviance:      5.545 
Residual Deviance: 5.545        AIC: 9.545 
> predict(fit,newdata=data.frame(x=1:2))
            1             2             3             4 
-1.110223e-16 -1.110223e-16            NA            NA 
Warning message:
'newdata' had 2 rows but variable(s) found have 4 rows
> predict(fit,newdata=data.frame(x=1:5))
            1             2             3             4 
-1.110223e-16 -1.110223e-16 -1.110223e-16 -1.110223e-16 
Warning message:
'newdata' had 5 rows but variable(s) found have 4 rows
>

HTH,

Chuck

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