```Date: Fri, 23 Sep 2005 19:47:45 +0200 Reply-To: Karl Koch Sender: "SPSSX(r) Discussion" From: Karl Koch Subject: Re: Regresssion Plot in SPSS Content-Type: text/plain; charset="iso-8859-1" Yes, I know that. But why does is go lower then 1 even if it was never trained for that? I am just wondering and would like to know curiously-wise. Not becuase it is a major problem for me... Perpaps you have an idea? Or perhaps there is not general explaination and it depends on the model itself? Karl > --- Ursprüngliche Nachricht --- > Von: Hector Maletta > An: SPSSX-L@LISTSERV.UGA.EDU > Betreff: Re: Regresssion Plot in SPSS > Datum: Fri, 23 Sep 2005 13:52:52 -0300 > > Karl, > Since the coefficients of A and C are negative, the predicted value when A > and C are at their maximum is actually the MINIMUM predicted value, in > this > case 0.967 which is close to the minimum observed value of 1. When A and C > are at their minimum value of 0, the predicted value of Y would equal the > constant, 4.16, which is less than the maximum value of Y but within the > permissible range of 1 to 6. Other combinations would give predicted > values > between 0.967 and 4.16. > > Hector > > > > > -----Original Message----- > > From: Karl Koch [mailto:TheRanger@gmx.net] > > Sent: Friday, September 23, 2005 1:42 PM > > To: Hector Maletta; Mailinglist SPSS > > Subject: RE: Regresssion Plot in SPSS > > > > Hello all, > > > > I have now a regression model that does exclude the > > non-significant second factor (B) as it was suggested earlier > > on this discussion. To recall the earlier discussion, I had > > three factors A, B, and C. B, however turned out to be > > non-significant. The final regression (non-standarized) > > equation looks like now like this: > > > > Y = 4.16 - 0.778 A - 1.637 C > > > > The original scale of the dependent variable (Y) is > > contineous and but limited between 1.0 and 6.0. The following > > list is the range of values for A and C: > > > > A = {0,1,2} > > C = {0,1} > > > > However when using the equation with the most extreme values > > for A (=2) and C (=1) I get a result of 0.967. This value is > > lower than the minimum value of the orginal scale of the > > dependent variable. I am wondering why this is... The > > prediction should actually not go below the theoretical > > minimum of the scale especially since this was never learned > > from previous data. Is this the appearance of some sort of > > error (espsilon) ? > > > > Can somebody explain that? > > > > Kind Regards, > > Karl > > > > > > > > > --- Ursprüngliche Nachricht --- > > > Von: "Hector Maletta" > > > An: "'Karl Koch'" , > > > Betreff: RE: Regresssion Plot in SPSS > > > Datum: Wed, 21 Sep 2005 17:05:28 -0300 > > > > > > Karl, > > > As you can see from your own results, standardized > > coefficients do not > > > add up to 1. Each standardized coefficient (beta) is the expected > > > change in Y, measured in standard deviations, for each > > increase of one > > > std deviation in X. There is no reason for these > > coefficients to add up to 1. > > > The advantage of beta over b is simply that they are comparable to > > > each other, and across studies, because they are independent of the > > > unit of measurement and the distributional peculiarities of each > > > variable, since all are measured in each variable's own standard > > > deviation units. On the other hand, they are relative to the std > > > deviation and are less understandable for readers, who may > > understand > > > better the raw b coefficients (so much increase in Y for each unit > > > increase in X, both measured in their natural units). > > > > > > Hector > > > > > > > -----Original Message----- > > > > From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On > > > > Behalf Of Karl Koch > > > > Sent: Wednesday, September 21, 2005 4:40 PM > > > > To: SPSSX-L@LISTSERV.UGA.EDU > > > > Subject: Re: Regresssion Plot in SPSS > > > > > > > > The standardized coefficients would then be what I am > > looking for. I > > > > need a parameter that adds up to 1.0 which I can directly > > assign to > > > > the independent variables. > > > > > > > > Karl > > > > > > > > > --- Ursprüngliche Nachricht --- > > > > > Von: Vishal Dave > > > > > An: SPSSX-L@LISTSERV.UGA.EDU > > > > > Betreff: Re: Regresssion Plot in SPSS > > > > > Datum: Wed, 21 Sep 2005 13:53:29 -0500 > > > > > > > > > > Karl, > > > > > > > > > > Since your variables are not standardized, the coefficients > > > > won't add > > > > > up to 1.0. You have to covert the variables in > > > > standardized variables > > > > > and > > > > then > > > > > run the regression model. It will give you model with > > > > intercept = 0 > > > > > and > > > > > sum(coefficients) = 1. This will also take care of having > > > > different > > > > > non-standardized variables with different mean and SD. > > > > > > > > > > Vishal. > > > > > > > > > > > > > > > > > > > > -----Original Message----- > > > > > From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] > > > > On Behalf > > > > > Of Karl Koch > > > > > Sent: Wednesday, September 21, 2005 12:48 PM > > > > > To: SPSSX-L@LISTSERV.UGA.EDU > > > > > Subject: Re: Regresssion Plot in SPSS > > > > > > > > > > So, what you are saying is I have to create first a new > > regression > > > > > model that only includes A and C. Then only use the > > unstandarized > > > > > regression coefficients. Did I understand you correctly? > > > > > > > > > > What is the difference to the standarized coefficients? Do the > > > > > standarized coefficients somehow add up to 1.0 so that > > they can be > > > > > seen as percentage of magnitiude? > > > > > > > > > > Kind Regards, > > > > > Karl > > > > > > > > > > > --- Ursprüngliche Nachricht --- > > > > > > Von: "Swank, Paul R" > > > > > > An: SPSSX-L@LISTSERV.UGA.EDU > > > > > > Betreff: Re: Regresssion Plot in SPSS > > > > > > Datum: Wed, 21 Sep 2005 12:35:19 -0500 > > > > > > > > > > > > No, you are using the unstandardized intercept but the > > > > standardized > > > > > > regression coefficients. And because B may bias the > > weights for > > > > > > A and C, > > > > > you need > > > > > > to run the regression again without B. The coefficients > > > > for Aand C > > > > > > will likely change. Then use the unstandardized > > > > coefficients for the > > > > > regression > > > > > > equation. > > > > > > > > > > > > > > > > > > Paul R. Swank, Ph.D. > > > > > > Professor, Developmental Pediatrics Director of > > Research, Center > > > > > > for Improving the Readiness > > > > of Children > > > > > > for Learning and Education (C.I.R.C.L.E.) Medical School > > > > UT Health > > > > > > Science Center at Houston > > > > > > > > > > > > -----Original Message----- > > > > > > From: Karl Koch [mailto:TheRanger@gmx.net] > > > > > > Sent: Wednesday, September 21, 2005 10:36 AM > > > > > > To: Swank, Paul R; Mailinglist SPSS > > > > > > Subject: RE: Regresssion Plot in SPSS > > > > > > > > > > > > Hello Paul, > > > > > > > > > > > > Yes, I agree. Given the fact that now I only have two > > > > paramters left > > > > > > (=being significant), is this the correct equation > > > > (keeping in mind > > > > > > the > > > > > table > > > > > > below)? > > > > > > > > > > > > Y = 4.195 - 0.319 * A - 0.442 * C + e > > > > > > > > > > > > What would be e in this case? I have standard erros for each > > > > > parameter... > > > > > > > > > > > > Kind Regards, > > > > > > Karl > > > > > > > > > > > > > > ---------------------------------------------------------------- > > > > > > Model Unstd. Coeff. Std. Coeff. t > > Sig. > > > > > > B Std. Error Beta > > > > > > > > ----------------------------------------------------------------- > > > > > > 1(Constant) 4.195 .070 > > 58.971 .000 > > > > > > A -.779 .042 -.319 > > -18.278 .000 > > > > > > B -.028 .046 -.010 > > -.618 .534 > > > > > > C -1.635 .064 -.442 > > -25.354 .000 > > > > > > > > ---------------------------------------------------------------- > > > > > > - > > > > > > > > > > > > > > > > > > > > > > > > > > Drop B from the model first as it could bias the > > > > parameters for A > > > > > > > and > > > > > C. > > > > > > > > > > > > > > > > > > > -- > > > > > > 5 GB Mailbox, 50 FreeSMS http://www.gmx.net/de/go/promail > > > > > > +++ GMX - die erste Adresse für Mail, Message, More +++ > > > > > > > > > > > > > > > > -- > > > > > 5 GB Mailbox, 50 FreeSMS http://www.gmx.net/de/go/promail > > > > > +++ GMX - die erste Adresse für Mail, Message, More +++ > > > > > > > > > > > > > -- > > > > 5 GB Mailbox, 50 FreeSMS http://www.gmx.net/de/go/promail > > > > +++ GMX - die erste Adresse für Mail, Message, More +++ > > > > > > > > -- > > > > Lust, ein paar Euro nebenbei zu verdienen? 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