From: Marwan Khawaja <mk36_at_aub.edu.lb>

Date: Wed 04 Jan 2006 - 20:47:55 EST

Marwan Khawaja http://staff.aub.edu.lb/~mk36

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Wed Jan 04 21:01:20 2006

Date: Wed 04 Jan 2006 - 20:47:55 EST

Dear Bob,

The reasons you mentioned are supposedly good features in R -- not giving
lots of output you do not necessarily need. I guess the question is why do
you want R to produce what you get from SPSS? SPSS is hardly a gold
standard in statistical software.

But I agree that it is quite difficult for users of SPSS to unlearn SPSS (or
SAS) while using R.

Best Marwan

Marwan Khawaja http://staff.aub.edu.lb/~mk36

> -----Original Message-----

*> From: r-help-bounces@stat.math.ethz.ch
**> [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Bob Green
**> Sent: Wednesday, January 04, 2006 3:37 AM
**> To: r-help@stat.math.ethz.ch
**> Subject: Re: [R] A comment about R:
**>
**>
**> >Hello,
**>
**>
**> >Unlike most posts on the R mailing list I feel qualified to
**> comment on
**> >this one. For about 3 months I have been trying to learn
**> use R, after
**> >having used various versions of SPSS for about 10 years.
**>
**>
**> I think it is far too simplistic to ascribe non-use of R to
**> laziness. This may well be the case for some, however, I
**> have read 5-6 books on R, waded through on-line resources,
**> read the documentation and asked multiple questions via
**> e-mails - and still find even some of the basics very difficult.
**>
**> There are several reasons for this:
**>
**> 1. For some tasks R is extremely user-unfriendly. Some
**> comparative examples:
**>
**> (a) In running a chi-square analysis in SPSS the following
**> syntax is included
**>
**> /STATISTIC=CHISQ
**> /CELLS= COUNT EXPECTED ROW COLUMN TOTAL RESID .
**>
**> this produces expected and observed counts, row & column
**> percentages, residuals, chi-square & Fisher's exact test +
**> other output.
**>
**> In R, it is a herculean task to produce similar output . It
**> certainly, can't be produced in 2 lines as far as I can tell.
**>
**> (b) in SPSS if I want to compare multiple variables by a
**> single dependent variable this is readily performed
**>
**> CROSSTABS
**> /TABLES=baserdis baserenh basersoc baseradd socbest
**> disbest entbest addbest worsdis worsphy by group
**>
**> I used the chi-square example again, but the same applies for
**> a t-test. I started looking into how to do something similar
**> in R, with the t-test command but gave up. R does force the
**> user to take a more considered approach to analysis.
**>
**> (c) To obtain a correlation matrix in R with the correlation
**> & p-value is no simple task -
**>
**> In SPSS this is obtained via:
**>
**> GET
**> FILE='D:\a study\data\dat\key data\master data.sav'.
**> NONPAR CORR
**> /VARIABLES= goodnum badnum good5 bad5 avfreq avdayamt
**> /PRINT=KENDALL TWOTAIL
**> /MISSING=PAIRWISE .
**>
**> In R something like this is required -
**>
**> > by(mydat, mydat$group, function(x) {
**> + nm <- names(x)
**> + rho <- matrix(, 6, 2)
**> + rho.nm <- matrix(, 6, 2)
**> + k <- 1
**> + for(i in 2:4) {
**> + for(j in (i + 1):5) {
**> + x.i <- x[, i]
**> + x.j <- x[, j]
**> + ct <- cor.test(x.i, x.j, method=c("kendall") , alternative
**> + =c("two-sided")) rho[k, 1] <- ct$estimate rho[k, 2] <-
**> + round(ct$p-value, 3) rho.nm[k, ] <- c(nm[i], nm[j]) k <- k
**> + 1 } } rho
**> + <- cbind(as.data.frame(rho.nm), as.data.frame(rho))
**> + names(rho) <- c("freq.i", "freq.j", "cor", "p-value") rho
**> + })
**>
**> 2) It is not always clear what the output produced by R, is.
**> The Mann-Whitney U-test is a good example. In R, it seems a
**> standardised value is obtained. I was advised that it is easy
**> enough to check this as R is open-source, but at least for
**> me, I don't believe I would understand this code anyway. It
**> is confusing when comparative programs such as R and SPSS
**> produce dis-similar results. For the user it is important to
**> be able to fairly easily reconcile such differences, to
**> engender confidence in results.
**>
**> 3) I find the help files in R quite difficult to understand.
**> For example, see help(t.test). It is almost assumed by the
**> examples that you know what to do. Personally, I would find
**> some form of simple decision tree easier -e.g. If you want to
**> perform a t-test with the dependent variable in one column
**> and the dependent use in another use t.test(AVFREQ~GROUP) .
**> If you want to perform a t-test with the dependent variable
**> in separate columns (each column representing a different
**> group) use - t.test(AVFREQ1, AVFREQ2) .
**>
**> 4) My initial approach to using R, was to run commands I had
**> used commonly in SPSS and compare the results. I have only
**> got as far as basic ANOVA.
**> This has been time-consuming and at times it has been
**> difficult to obtain advice. Some people on the R list have
**> been extremely generous with their time and knowledge, and I
**> have much appreciated this assistance. At other times I see
**> responses met with something like arrogance. With the
**> sophistication of R, there is also an elitism. This is a
**> barrier to R being more widely accepted and used.
**>
**> 5) differences in terminology - this is just part of the
**> learning process, but I still found it took quite some time
**> to work out simple commands and what different analyses were called.
**>
**> 6) system administrators may be wary of freeware.
**>
**> No doubt for the sophisticated user, my comments may seem
**> trite and easily resolved, however I believe my comments have
**> some relevance as to why R is not more readily used or accepted.
**>
**>
**> Bob Green
**>
**> ______________________________________________
**> R-help@stat.math.ethz.ch mailing list
**> https://stat.ethz.ch/mailman/listinfo/r-help
**> PLEASE do read the posting guide!
**> http://www.R-project.org/posting-guide.html
*

>

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Wed Jan 04 21:01:20 2006

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