From the messages you get I do not believe this is a recent version of
read.spss (message 2 no longer appears), and you haven't followed the
posting guide and told us. However, your message 3 does still appear, and
that might be significant.
A small anount of googling came up with
https://stat.ethz.ch/pipermail/r-help/2008-April/159342.html
and I guess this is the same issue. A quick look at the code for
read.spss() suggests that the information on user-defined missing values
is being read in, and that there are yet more possible types of
missingness (only some of which I understand). So what is needed is to
return that info to the R user: now we have an example at least something
shold be possible.
On Fri, 1 Aug 2008, Jeroen Ooms wrote:
There is a problem when importing an spss-file containing explicitly declared
missing values in R using the read.spss function from the foreign package.
I'm not sure these problems are the same in every version of spss, I am
using the latest version 16.0.2.
I included http://www.nabble.com/file/p18776776/missingdata.sav
missingdata.sav and http://www.nabble.com/file/p18776776/frequencies.jpg
frequencies.jpg as an example. The data contains 3 types of missing data: 2
are explicitly declared as a missing-value ('8' = NA and '9' = NAP), the
third type are the system missings. When this file is imported in R, only
the system missings are recognized as missing values, the others are just
imported as levels in the nominal case, and as (labeled) real values 8 and 9
in the continuous case. There are also no attributes in the object returned
by read.spss that contain information about which values/levels are the
missing values; their missingness seems to be completely ignored by the
function.
Is there some way or other function to be able to import spss files, with an
option that replaces all missing values with <NA>'s in R? Of course this
comes with the trade-off of losing the meaning of the missingness when there
are multiple types of missingness, but I think this is far less harmfull
than treating all missing values as normal values.
If the missingness information were returned others are likely to
disagree, especially for factors. All that is 'harmfull' is that you are
not told that value labels NA and NAP were to be regarded as 'missing' in
SPSS. We've no idea whether if would be a more or less egregious choice
to map them to R's NA, and certainly are not in a position to assert 'far
less harmfull' in general.
[code]
mydata <- read.spss("c:/users/jeroen/desktop/missingdata.sav",
to.data.frame=T)
Warning messages:
1: In read.spss("c:/users/jeroen/desktop/missingdata.sav", to.data.frame =
T) :
c:/users/jeroen/desktop/missingdata.sav: File-indicated character
representation code (1252) looks like a Windows codepage
2: In read.spss("c:/users/jeroen/desktop/missingdata.sav", to.data.frame =
T) :
c:/users/jeroen/desktop/missingdata.sav: Unrecognized record type 7,
subtype 16 encountered in system file
3: In read.spss("c:/users/jeroen/desktop/missingdata.sav", to.data.frame =
T) :
c:/users/jeroen/desktop/missingdata.sav: Unrecognized record type 7,
subtype 20 encountered in system file
mydata
SUBJECT CATEGORI CONTINUO
1 1 yes 3.11
2 2 yes 2.10
3 3 yes 5.34
4 4 yes 1.54
5 5 yes 3.89
6 6 no 2.98
7 7 no 4.53
8 8 no 1.98
9 9 no 3.68
10 10 no 2.94
11 11 NA 8.00
12 12 NA 8.00
13 13 NA 8.00
14 14 NA 8.00
15 15 NA 8.00
16 16 NAP 9.00
17 17 NAP 9.00
18 18 NAP 9.00
19 19 NAP 9.00
20 20 NAP 9.00
21 21 <NA> NA
22 22 <NA> NA
23 23 <NA> NA
24 24 <NA> NA
25 25 <NA> NA
is.na(mydata$CONTINUO)
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE
TRUE
is.na(mydata$CATEGORI)
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE
TRUE
summary(mydata)
SUBJECT CATEGORI CONTINUO
Min. : 1 yes :5 Min. :1.540
1st Qu.: 7 no :5 1st Qu.:3.078
Median :13 NA :5 Median :6.670
Mean :13 NAP :5 Mean :5.854
3rd Qu.:19 NA's:5 3rd Qu.:8.250
Max. :25 Max. :9.000
NA's :5.000
[/code]
--
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http://www.nabble.com/importing-explicitly-declared-missing-values-in-read.spss-%28foreign%29-tp18776776p18776776.html
Sent from the R devel mailing list archive at Nabble.com.
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Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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