Dear David and Paul, Thank you for your answers!
Yes, Paul, I checked the SPSS file and the numerical variables that had no value labels assigned to them in SPSS got the right measurements in R after importing, namely "interval". The two variables that had the measurement "nominal" in R allthough they contain exclusively numbers have value labels assigned to them in SPSS, namely -3 for a filter. So now I know why this is happening, thank you very much! David, I used: sapply(mz,function(a)measurement(a)) to check the measurements. "Nominal" and "interval" are in fact special memisc terminology - the first for categorical variables, the second for numeric variables. Thank's for this suggestion of using measurement(mz$age_variable) <- "interval" to change the measurement which is in accordance whith the R logic, so it is probably always a good way to try something like this even without knowing the package very well. Cheers, Marion David Winsemius <https://plus.google.com/u/0/112644179894492041799?prsrc=4> Dear list members, > > I have got another problem. I imported an SPSS file with the Memisc package > using the following commands: > > mz <- spss.system.file("myspssfile.sav") > > mz <- subset(mz,select=c( > bsex,balt,xurb,dtaet,kartab,bgeb,boseit,bgeblan,xnuts2,kausb,xerwstat, > asbper,asbhh,ajahr,aquartal,bstaat,xwieoft,gew1,apkz,bpkzm,bpkzv)) > The memisc package help file for spss.system.file() (actually labeled "importers") says that there is an S4 method for "subset" there does not seem to be a separate page describing its behavior or values > Afterwards I checked the measurements of the variables > What does that phrase mean? What code did you actually use? and they are all > right for most of them (e.g. the variable containing the sex of a person is > "nominal" and the variable containing the year is "interval"). For two of > the variables the measurement is not o.k, though. They exclusively contain > numbers in the SPSS file (e.g. the age of a person) - and no NAs - but have > got the measurement "nominal"! > Hard to say. There is no R storage mode that is called "nominal". Perhaps some sort of memisc-specific terminology? Or perhaps something in your spss dataset... to which you have not provided access? Or the default setting for the spss.system.file access method? I know that the Hmisc package's describe() function will report out a variable as though it were categorical if there are only 8 or fewer unique values. After looking at further help pages and trying the help pages code, I am guessing that some of my puzzlement might be answered by reading the vignettes, but you can do that yourself. Here's a hackish guess ... try: ?measurement measurement(mz$age_variable) <- "interval" # where age_variable is the unstated item in that "select" list Paul Bivand 26. Jul (vor 1 Tag) an r-help; Marion Nachricht übersetzen Deaktivieren für: Englisch David's ?measurement measurement(mz$age_variable) <- "interval" # where age_variable is the unstated item in that "select" list is what I use in similar circumstances. Where it seems to come from is the SPSS users habit of setting value labels on various categories of user-missing values - so a survey will commonly have no actual missings (in spss, system-missing) but -9 as 'refused', -8 as 'not contactable' and so on. The importer picks up the existence of value labels and sets the mode as "nominal" - which gets transformed into factor in R usage - using base read.spss would be likely to read these in as factor. For analysis purposes, these values would be likely to be NA, but it may be important to record that you were making that change. [[alternative HTML version deleted]]
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