Thanks for the reply. The mistake in 1 resulted to be due to using a
different number of decimal places in the data.
As regards 2, will check it out again.
Thanks again.
Fiona Sammut wrote:
Hi all,
1. I am doing some data analysis using both R and SPSS, to get used
to both software packages. I had performed linear regression in R
and SPSS for a number of times before this last one and the resulting
coefficient values always matched. However, this last data set I was
analyzing using simple linear regression and using the command
lm(y~x), gave me different readings from R and SPSS:
R: y= 33.803 + 6.897x
SPSS: y= 47.589 + 6.263x
I have no doubts regarding the procedure employed in SPSS and I am
sure I am using the same dataset for both software packages.
My guess is you have missing values defined in SPSS but don't have
those same values set to NA in R. Have you requested basic
descriptive statistics in both programs and found that they match?
Also, perhaps x a factor in R. If so, how are its contrasts set?
2. Correct me if I am wrong, but from what I've read, it seems that
the command /anova /in R works out an analysis of variance without
including the intercept. Is that so? Cause again I am working out
an anova in R and SPSS and I got different resulting sums of squares
and different degrees of freedom. I thought this was because one
package is working with an intercept and the other isn't.
I don't think this has anything to do with the discrepancy.
Can anyone enlighten me as to what might have happened in both 1. and
2. please? Are they both due to my poor knowledge of R or could
occurences as above happen?
3. I would like a reference to a command which can be used to fit a
distribution to a disrete distribution.
library(MASS)
?fitdistr
Thanks in advance for your consideration.
- Fiona Sammut
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