Hello Andrea,
I don't know if I can help you (probably not, I'm a beginner myself),
but you that you should make it a lot easier for those that can if you
post a self-contained script in this forum that shows what you're
trying to do. Use dput() to dump your dataset in text form.
Good luck,
robert
On Tue, May 15, 2012 at 10:49 PM, Andrea Sica <aerdna.sica at gmail.com>
wrote:> Dear all,
>
> I hope to be the clearest I can.
> Let's say I have a dataset with 10 variables, where 4 of them represent
for
> me a certain phenomenon that I call Y.
> The other 6 represent for me another phenomenon that I call X.
>
> Each one of those variables (10) contains 37 units. Those units are just
> the respondents of my analysis (a survey).
> Since all the questions are based on a Likert scale, they are qualitative
> variables. The scale is from 0 to 7 for all of
> them, but there are "-1" and "-2" values where the
answer is missing. Hence
> the scale goes actually from -2 to 7.
>
> What I want to do is to calculate the regression between my Y (which
> contains 4 variables in this case and 37 answers
> for each variable) and my X (which contains 6 variables instead and the
> same number of respondents). I know that for
> qualitative analyses I should use Anova instead of the regression, although
> I have read somewhere that it is even possible
> to make the regression.
>
> Until now I have tried to act this way:
>
__________________________________________________________________________________________________________
>> apply(Y, 1, function(Y) mean(Y[Y>0])) #calculate the average per
rows
> (respondents) without considering the negative values
>
>> Y.reg<- c(apply(Y, 1, function(Y) mean(Y[Y>0]))) #create the
vector Y,
> thus it results like 1 variable with 37 numbers
>
>> apply(X, 1, function(X) mean(X[X>0]))
>
>> X.reg<- c(apply(X, 1, function(X) mean(X[X>0]))) #create the
vector
> X, thus it results like 1 variable with 37 numbers
>
>> reg1<- lm(Y.reg~ X.reg) #make the first regression
>> summary(reg1) #see the results
>
> Call:
> lm(formula = Y.reg ~ X.reg)
>
> Residuals:
> ? ? Min ? ? ? ? 1Q ? ? ? Median ? ? ?3Q ? ? ? Max
> -2.26183 -0.49434 -0.02658 ?0.37260 ?2.08899
>
> Coefficients:
> ? ? ? ? ? ? ? ? Estimate Std. Error ? t value ? Pr(>|t|)
> (Intercept) ? 4.2577 ? ? 0.4986 ? ? ?8.539 ? ?4.46e-10 ***
> X.reg ? ? ? ? ?0.1008 ? ? 0.1282 ? ? ?0.786 ? ?0.437
> ---
> Signif. codes: ?0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
>
> Residual standard error: 0.7827 on 35 degrees of freedom
> Multiple R-squared: 0.01736, ? ?Adjusted R-squared: -0.01072
> F-statistic: 0.6182 on 1 and 35 DF, ?p-value: 0.437
>
>> layout(matrix(1:4,2,2)) #graphical approach
>> plot(reg1)
>
> please see the pfd() function attached.
>
________________________________________________________________________________________________________
>
> But as you can see, although I do not use Y as composed by 4 variables and
> X by 6, and I do not consider the negative values
> too, I get a very low score as my R^2.
>
> If I act with anova instead I have this problem:
>
________________________________________________________________________________________________________
>> Ymatrix<- as.matrix(Y)
>> Xmatrix<- as.matrix(X) #where both this Y and X are in their first
form,
> thus composed by more variables (4 and 6) and with
> #negative values as well.
>
>> Errore in UseMethod("anova") :
> ?no applicable method for 'anova' applied to an object of class
> "c('matrix', 'integer', 'numeric')"
>
________________________________________________________________________________________________________
>
> To be honest, a few days ago I succeeded in using anova, but unfortunately
> I do not remember how and I did not save the
> command anywhere.
>
> What I would like to know is:
>
> - First of all, am I wrong in how I approach to my problem?
> - What do you think about the regression output?
> - Finally, how can I do to make the anova? If I have to do it.
>
> I really hope I have been clear. Thank you all for any kind of help.
>
> Best,
>
> Andrea
>
> ? ? ? ?[[alternative HTML version deleted]]
>
>
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