David (and the last paragraph for Bruce),
Your data generation program produces X1 which has four levels and X2 which has two levels. Therefore, your MIXED code should look like this (for my linear trend interaction code to produce an estimable function): MIXED Y BY X2 X1 /FIXED=X2 X1 X2*X1 | SSTYPE(3) /METHOD=REML /PRINT=SOLUTION /TEST = 'linear trend x2_1' x1 -3 -1 1 3 x2*x1 -3 -1 1 3 0 0 0 0 /TEST = 'linear trend x2_2' x1 -3 -1 1 3 x2*x1 0 0 0 0 -3 -1 1 3 /TEST = 'linear trend interaction' x2*x1 -3 -1 1 3 3 1 -1 -3. Now, whether this is what you are interested in testing is a whole other matter. See my posts to Bruce to see exactly what these TEST statements are producing. You might also find those other posts useful regarding how I arrived at the linear trend coefficients and how GLM has a similar sub-command that utilizes the L MATRIX. (Apologies for the multiple posting previously--couldn't fix the formatting) With regard to Bruce's data, I noticed that for the interaction linear trend test, the test statistics, SS, and df are exactly the same between GLM (via LMATRIX) and MANOVA. This provides additional confirmation that interaction linear trend test proposed previously is conducting Bruce's test of interest. It should be noted that the LMATRIX from GLM automatically provides the SS that Bruce stated was important to him.
HTH, Ryan On Fri, Oct 28, 2011 at 10:09 AM, David Marso <[hidden email]> wrote: > > INPUT PROGRAM. > LOOP ID=1 TO 1000. > COMPUTE X1=TRUNC(UNIFORM(4))+1. > COMPUTE X2=TRUNC(UNIFORM(2))+1. > end case. > end loop. > end file. > end input program. > > DO IF X2=1. > COMPUTE Y=NORMAL(1)+10. > ELSE. > COMPUTE Y=NORMAL(1)+ X1*2. > END IF. > RECODE X1 (1=-0.670820393249937)(2= -0.223606797749979 )(3= > 0.223606797749979 )(4=0.670820393249937) INTO LX1. > RECODE X2 (1=-0.707106781186547)(2= 0.707106781186547) INTO LX2. > COMPUTE LX1LX2=LX1*LX2. > > MEANS TABLES=y By x2 BY x1 . > REGRESSION / DEP Y / METHOD ENTER LX1 LX2 LX1LX2. > MANOVA Y WITH LX1 LX2 LX1LX2. > > manova y by x1(1,4) x2(1,2) / > contrast(x1)=poly/ > contrast(x2)=poly/ > partition(x1)=(1,1)/ > print=design/ > DESIGN=x1 x2 x1(1) by x2. > > MIXED Y BY X1 X2 > /FIXED=X1 X2 X1*X2 | SSTYPE(3) > /METHOD=REML > /PRINT=SOLUTION > /TEST = 'Linear X1' X1 -0.670820393249937 -0.223606797749979 > 0.223606797749979 0.670820393249937 > /TEST = 'Linear X2' X2 -0.707106781186547 0.707106781186547 > /TEST = 'Linear Trend Interaction' X1*X2 0.474341649025257 > -0.474341649025257 0.158113883008419 -0.158113883008419 -0.158113883008419 > 0.158113883008419 -0.474341649025257 0.474341649025257 . > > > > Bruce Weaver wrote: > > > > Yes, that's right. > > > > I forgot to mention when responding to your earlier post that another > > reason for not using MIXED (with TEST) was that I preferred OLS to MLE, > > because in a balanced design, the SS for the polynomial components of the > > A*B interaction will add up exactly to the SS(A*B). I doubt that will be > > the case with MLE. > > > > I've still not had time to try either method--too many meetings. Will get > > to it later today or tomorrow. > > > > Cheers, > > Bruce > > > > > > > > R B wrote: > >> > >> You do have exactly two levels for A and four levels for B, right? > >> > >> Ryan > >> > >> On Thu, Oct 27, 2011 at 7:23 AM, Bruce Weaver <bruce.weaver@> > >> wrote: > >>> Aha...that looks like what I was after, Tony. I'll give it a try. > >>> Ryan, > >>> I'll give your /TEST for MIXED method a try too, and compare the > >>> results. > >>> > >>> Thanks guys. > >>> > >>> > >>> > >>> Anthony Babinec wrote: > >>>> > >>>> I think that you have to use MANOVA. GLM uses "set to 0" contrasts > >>>> while > >>>> MANOVA uses "sum to 0" contrasts. Here is a short MANOVA example > >>>> that you can imitate. I just took some "nonsense" variables from the > >>>> General Social Survey and recode hhsize as 1=1, 2=2, 3 thru 11=3. > >>>> The design shows the linear by linear interaction as an example. > >>>> > >>>> manova educ by hhsize(1,3) race(1,3) / > >>>> contrast(hhsize)=poly/ > >>>> contrast(race)=poly/ > >>>> partition(hhsize)=(1,1)/ > >>>> partition(race)=(1,1)/ > >>>> print=design/ > >>>> DESIGN=hhsize race hhsize(1) by race(1). > >>>> > >>>> Tony Babinec > >>>> tbabinec@ > >>>> > >>>> ===================== > >>>> To manage your subscription to SPSSX-L, send a message to > >>>> LISTSERV@.UGA (not to SPSSX-L), with no body text except the > >>>> command. To leave the list, send the command > >>>> SIGNOFF SPSSX-L > >>>> For a list of commands to manage subscriptions, send the command > >>>> INFO REFCARD > >>>> > >>> > >>> > >>> ----- > >>> -- > >>> Bruce Weaver > >>> bweaver@ > >>> http://sites.google.com/a/lakeheadu.ca/bweaver/ > >>> > >>> "When all else fails, RTFM." > >>> > >>> NOTE: My Hotmail account is not monitored regularly. > >>> To send me an e-mail, please use the address shown above. > >>> > >>> -- > >>> View this message in context: > >>> http://spssx-discussion.1045642.n5.nabble.com/Polynomial-contrast-for-interaction-in-completely-between-Ss-design-tp4941355p4942677.html > >>> Sent from the SPSSX Discussion mailing list archive at Nabble.com. > >>> > >>> ===================== > >>> To manage your subscription to SPSSX-L, send a message to > >>> LISTSERV@.UGA (not to SPSSX-L), with no body text except the > >>> command. To leave the list, send the command > >>> SIGNOFF SPSSX-L > >>> For a list of commands to manage subscriptions, send the command > >>> INFO REFCARD > >>> > >> > >> ===================== > >> To manage your subscription to SPSSX-L, send a message to > >> LISTSERV@.UGA (not to SPSSX-L), with no body text except the > >> command. To leave the list, send the command > >> SIGNOFF SPSSX-L > >> For a list of commands to manage subscriptions, send the command > >> INFO REFCARD > >> > > > > > -- > View this message in context: http://spssx-discussion.1045642.n5.nabble.com/Polynomial-contrast-for-interaction-in-completely-between-Ss-design-tp4941355p4946042.html > Sent from the SPSSX Discussion mailing list archive at Nabble.com. > > ===================== > To manage your subscription to SPSSX-L, send a message to > [hidden email] (not to SPSSX-L), with no body text except the > command. To leave the list, send the command > SIGNOFF SPSSX-L > For a list of commands to manage subscriptions, send the command > INFO REFCARD |
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Yes, LMATRIX does it. For the sake of tying a bow on this thread, here is the MANOVA syntax I posted earlier, and UNIANOVA syntax that gives tests (and SS) for the linear, quadratic and cubic components of the A*B interaction:
MANOVA Y by A(0,1) B(1,4) / contrast(A)=poly/ contrast(B)=poly/ partition(B)=(1,1,1)/ print=design/ DESIGN=A B A by B(1) A by B(2) A by B(3) . UNIANOVA Y BY A B /LMATRIX = 'Interaction Linear Trend' A*B -3 -1 1 3 3 1 -1 -3 /LMATRIX = 'Interaction Quadratic Trend' A*B 1 -1 -1 1 -1 1 1 -1 /LMATRIX = 'Interaction Cubic Trend' A*B -1 3 -3 1 1 -3 3 -1 /DESIGN=A B A*B. For the data set I was using, both of these yield the following: SS(A*B) = 99.400 SS(linear component of A*B) = 98.000 SS(quadratic component of A*B) = 0.900 SS(cubic component of A*B) = 0.500 % of interaction due to linear component = 98.0*100 / 99.4 = 98.6% I am still left wondering why this is not a bit easier to do for UNIANOVA. As I've mentioned before, one gets the polynomial components of the interaction term automatically when using GLM Repeated Measures. Thanks again to Tony, Ryan & David. Cheers, Bruce
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Bruce Weaver bweaver@lakeheadu.ca http://sites.google.com/a/lakeheadu.ca/bweaver/ "When all else fails, RTFM." PLEASE NOTE THE FOLLOWING: 1. My Hotmail account is not monitored regularly. To send me an e-mail, please use the address shown above. 2. The SPSSX Discussion forum on Nabble is no longer linked to the SPSSX-L listserv administered by UGA (https://listserv.uga.edu/). |
Dear list
My design is quite simple two independent variables A and B each with two levels(1 or 2).I performed ANOVA UNIANOVA y BY a b /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /PRINT = DESCRIPTIVE /CRITERIA = ALPHA(.05) /DESIGN =a b a*b . The interaction is significant and I want to test the simple effects of B. That is, to perform two contrasts the first between the two levels of B for A=1 and the second between the two levels of B for A=2. What is the syntax that I should use for this contrast? I will appreciate any help Thanks Kelly Saporta, Ph.D. Department of Education and Psychology The Open University, Ra'anana, Israel 43107 Phone: +972-9-7781456, Email: [hidden email] http://www.openu.ac.il/Personal_sites/kelli-saporta/ D ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
Keli,
Look at the Emmeans command in the documentation. Most basically, EMMEANS = TABLES(A*B) COMPARE(B). The comparison can also be done using the Lmatrix subcommand with which others are far more competent with than I am. Gene Maguin -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Keli Saporta Sent: Wednesday, March 07, 2012 2:08 AM To: [hidden email] Subject: syntax for contrasts Dear list My design is quite simple two independent variables A and B each with two levels(1 or 2).I performed ANOVA UNIANOVA y BY a b /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /PRINT = DESCRIPTIVE /CRITERIA = ALPHA(.05) /DESIGN =a b a*b . The interaction is significant and I want to test the simple effects of B. That is, to perform two contrasts the first between the two levels of B for A=1 and the second between the two levels of B for A=2. What is the syntax that I should use for this contrast? I will appreciate any help Thanks Kelly Saporta, Ph.D. Department of Education and Psychology The Open University, Ra'anana, Israel 43107 Phone: +972-9-7781456, Email: [hidden email] http://www.openu.ac.il/Personal_sites/kelli-saporta/ D ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
Thank you Gene
It worked very good. And another question (if you don’t mind) What if A has three levels? can I define specific contrasts by setting weights? What is the syntax? Thank you again Kelly Saporta, Ph.D. Department of Education and Psychology The Open University, Ra'anana, Israel 43107 Phone: +972-9-7781456, Email: [hidden email] http://www.openu.ac.il/Personal_sites/kelli-saporta/ -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Maguin, Eugene Sent: Wednesday, March 07, 2012 5:00 PM To: [hidden email] Subject: Re: syntax for contrasts Keli, Look at the Emmeans command in the documentation. Most basically, EMMEANS = TABLES(A*B) COMPARE(B). The comparison can also be done using the Lmatrix subcommand with which others are far more competent with than I am. Gene Maguin -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Keli Saporta Sent: Wednesday, March 07, 2012 2:08 AM To: [hidden email] Subject: syntax for contrasts Dear list My design is quite simple two independent variables A and B each with two levels(1 or 2).I performed ANOVA UNIANOVA y BY a b /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /PRINT = DESCRIPTIVE /CRITERIA = ALPHA(.05) /DESIGN =a b a*b . The interaction is significant and I want to test the simple effects of B. That is, to perform two contrasts the first between the two levels of B for A=1 and the second between the two levels of B for A=2. What is the syntax that I should use for this contrast? I will appreciate any help Thanks Kelly Saporta, Ph.D. Department of Education and Psychology The Open University, Ra'anana, Israel 43107 Phone: +972-9-7781456, Email: [hidden email] http://www.openu.ac.il/Personal_sites/kelli-saporta/ D ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
In reply to this post by Keli Saporta
In terms of the pure simple effects, Use effect coding instead of dummy coding. Otherwise, given what you want, you could also just reverse your dummy coding values each time you run it, this is not uncommon.
For the contrast table mentioned you will need to use LMatrix and you will need to create your contrast table to put it together. Example code would be as follows: /Lmatrix "test" A 0 0 A*B 1 -1 -1 1 The following link helped me learn how to do this. http://www.atlas.illinois.edu/support/stats/resources/spss/How_to_write_contrast_statements_in_SAS_and_SPSS.pdf You will ultimately have at least 2 lines below the Lmatrix subcommand. That command is put into your ANOVA anywhere above the last line of code. In the example code I gave, this compares the values of A at levels 1 and 2, when variable B is fixed at a base value of 0 (reference category). Matthew J Poes Research Data Specialist Center for Prevention Research and Development University of Illinois 510 Devonshire Dr. Champaign, IL 61820 Phone: 217-265-4576 email: [hidden email] -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Keli Saporta Sent: Wednesday, March 07, 2012 1:08 AM To: [hidden email] Subject: syntax for contrasts Dear list My design is quite simple two independent variables A and B each with two levels(1 or 2).I performed ANOVA UNIANOVA y BY a b /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /PRINT = DESCRIPTIVE /CRITERIA = ALPHA(.05) /DESIGN =a b a*b . The interaction is significant and I want to test the simple effects of B. That is, to perform two contrasts the first between the two levels of B for A=1 and the second between the two levels of B for A=2. What is the syntax that I should use for this contrast? I will appreciate any help Thanks Kelly Saporta, Ph.D. Department of Education and Psychology The Open University, Ra'anana, Israel 43107 Phone: +972-9-7781456, Email: [hidden email] http://www.openu.ac.il/Personal_sites/kelli-saporta/ D ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
In reply to this post by Keli Saporta
Kelly,
A 3X2 design can be depicted as follows:
Factor B 1 2 --------- 1 |a1b1|a1b2| Factor A 2 |a2b1|a2b2| 3 |a3b1|a3b2| --------- With that said, the following LMATRIX statements estimate the cell means: /lmatrix = 'a1b1' int 1 a 1 0 0 b 1 0 a*b 1 0 0 0 0 0 Using the statements above we could write the following pairwise contrasts:
/lmatrix = 'a1b1 MINUS a1b2' int 0 a 0 0 0 b 1 -1 a*b 1 -1 0 0 0 0
/lmatrix = 'a1b1 MINUS a2b1' int 0 a 1 -1 0 b 0 0 a*b 1 0 -1 0 0 0 /lmatrix = 'a1b1 MINUS a2b2' int 0 a 1 -1 0 b 1 -1 a*b 1 0 0 -1 0 0 /lmatrix = 'a1b1 MINUS a3b1' int 0 a 1 0 -1 b 0 0 a*b 1 0 0 0 -1 0 /lmatrix = 'a1b1 MINUS a3b2' int 0 a 1 0 -1 b 1 -1 a*b 1 0 0 0 0 -1 We could simplify the above statements by eliminating effects which have all zero coefficients as follows: /lmatrix = 'a1b1 MINUS a1b2' b 1 -1 a*b 1 -1 0 0 0 0 Here's a message I posted a while back which shows additional types of contrasts: http://www.listserv.uga.edu/cgi-bin/wa?A2=ind1012&L=spssx-l&P=R9561 I hope this gives you some idea of how the lmatrix works.
Ryan
2012/3/7 Keli Saporta <[hidden email]> Thank you Gene |
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Ryan, thanks for posting these helpful examples of LMATRIX. But note that I am having trouble getting the approach you used for obtaining cell means to work. I illustrate below, using one of your datasets.
* The data used below are from this post to SPSSX-L: http://www.listserv.uga.edu/cgi-bin/wa?A2=ind1012&L=spssx-l&P=R9561 data list list / ID Group Y. begin data 1 1 24 2 1 22 3 1 21 4 1 23 5 2 67 6 2 66 7 2 67 8 2 65 9 3 43 10 3 44 11 3 45 12 3 42 13 4 12 14 4 11 15 4 10 16 4 13 end data. * In another post to SPSSX-L, Ryan suggested using LMATRIX * as follows to obtain cell means for a two-factor (3x2) model * with factors called A and B: * /lmatrix = 'a1b1' int 1 a 1 0 0 b 1 0 a*b 1 0 0 0 0 0 * /lmatrix = 'a1b2' int 1 a 1 0 0 b 0 1 a*b 0 1 0 0 0 0 * /lmatrix = 'a2b1' int 1 a 0 1 0 b 1 0 a*b 0 0 1 0 0 0 * /lmatrix = 'a2b2' int 1 a 0 1 0 b 0 1 a*b 0 0 0 1 0 0 * /lmatrix = 'a3b1' int 1 a 0 0 1 b 1 0 a*b 0 0 0 0 1 0 * /lmatrix = 'a3b2' int 1 a 0 0 1 b 0 1 a*b 0 0 0 0 0 1 * I will try a variation on that to obtain the 4 group means * for my model. GLM Y BY Group /PRINT = PARAMETER /DESIGN = Group /LMATRIX = "G1" int 1 Group 1 0 0 0 /LMATRIX = "G2" int 1 Group 0 1 0 0 /LMATRIX = "G3" int 1 Group 0 0 1 0 /LMATRIX = "G4" int 1 Group 0 0 0 1 . * That does not work -- "int" is causing an error. * Having consulted the FM, I think that when one wishes * to include the intercept, one must do it via the keyword * ALL, as shown below. GLM Y BY Group /PRINT = PARAMETER /DESIGN = Group /LMATRIX = "G1" ALL 1 1 0 0 0 /LMATRIX = "G1" ALL 1 0 1 0 0 /LMATRIX = "G1" ALL 1 0 0 1 0 /LMATRIX = "G1" ALL 1 0 0 0 1 . * Use MEANS to verify that the group means are correct. means Y by group. ****** End of demo ****** . Ryan, are those LMATRIX commands including "int" working for you? Based on what I've seen (and perusal of the FM), I think they might have to be changed to: /lmatrix = 'a1b1' ALL 1 1 0 0 1 0 1 0 0 0 0 0 /lmatrix = 'a1b2' ALL 1 1 0 0 0 1 0 1 0 0 0 0 /lmatrix = 'a2b1' ALL 1 0 1 0 1 0 0 0 1 0 0 0 /lmatrix = 'a2b2' ALL 1 0 1 0 0 1 0 0 0 1 0 0 /lmatrix = 'a3b1' ALL 1 0 0 1 1 0 0 0 0 0 1 0 /lmatrix = 'a3b2' ALL 1 0 0 1 0 1 0 0 0 0 0 1 Thanks for clarifying. Bruce
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Bruce Weaver bweaver@lakeheadu.ca http://sites.google.com/a/lakeheadu.ca/bweaver/ "When all else fails, RTFM." PLEASE NOTE THE FOLLOWING: 1. My Hotmail account is not monitored regularly. To send me an e-mail, please use the address shown above. 2. The SPSSX Discussion forum on Nabble is no longer linked to the SPSSX-L listserv administered by UGA (https://listserv.uga.edu/). |
I just assumed "int" could be used in the same way it's used in the TEST subcommand in the MIXED procedure. I'm sure you are correct that "ALL" is the KEYWORD to replace "int". Seems silly to me to not allow the the specification of the intercept more directly but it is what it is. This is why I'm such a believer in using data when providing these types of answers. It ensures my assumptions are correct.
Anyway, the point I was making is that if you start by estimating the means, then any pairwise contrast can be easily obtain by subtracting like terms. From there you can test for diff of diff (which is not uncommon) by subtracting like terms from the pairwise contrasts. This approach reduces the possibility of writing the dreaded non-estimable functions. Often when one is unsure of how to write a contrast for the LMATRIX via GLM or MIXED, starting with estimating the means resolves any confusion. Good catch, Bruce. Sorry all. Ryan On Mar 9, 2012, at 9:57 AM, Bruce Weaver <[hidden email]> wrote: > Ryan, thanks for posting these helpful examples of LMATRIX. But note that I > am having trouble getting the approach you used for obtaining cell means to > work. I illustrate below, using one of your datasets. > > * The data used below are from this post to SPSSX-L: > http://www.listserv.uga.edu/cgi-bin/wa?A2=ind1012&L=spssx-l&P=R9561 > > data list list / ID Group Y. > begin data > 1 1 24 > 2 1 22 > 3 1 21 > 4 1 23 > 5 2 67 > 6 2 66 > 7 2 67 > 8 2 65 > 9 3 43 > 10 3 44 > 11 3 45 > 12 3 42 > 13 4 12 > 14 4 11 > 15 4 10 > 16 4 13 > end data. > > * In another post to SPSSX-L, Ryan suggested using LMATRIX > * as follows to obtain cell means for a two-factor (3x2) model > * with factors called A and B: > > * /lmatrix = 'a1b1' int 1 a 1 0 0 b 1 0 a*b 1 0 0 0 0 0 > * /lmatrix = 'a1b2' int 1 a 1 0 0 b 0 1 a*b 0 1 0 0 0 0 > * /lmatrix = 'a2b1' int 1 a 0 1 0 b 1 0 a*b 0 0 1 0 0 0 > * /lmatrix = 'a2b2' int 1 a 0 1 0 b 0 1 a*b 0 0 0 1 0 0 > * /lmatrix = 'a3b1' int 1 a 0 0 1 b 1 0 a*b 0 0 0 0 1 0 > * /lmatrix = 'a3b2' int 1 a 0 0 1 b 0 1 a*b 0 0 0 0 0 1 > > * I will try a variation on that to obtain the 4 group means > * for my model. > > GLM Y BY Group > /PRINT = PARAMETER > /DESIGN = Group > /LMATRIX = "G1" int 1 Group 1 0 0 0 > /LMATRIX = "G2" int 1 Group 0 1 0 0 > /LMATRIX = "G3" int 1 Group 0 0 1 0 > /LMATRIX = "G4" int 1 Group 0 0 0 1 > . > > * That does not work -- "int" is causing an error. > * Having consulted the FM, I think that when one wishes > * to include the intercept, one must do it via the keyword > * ALL, as shown below. > > GLM Y BY Group > /PRINT = PARAMETER > /DESIGN = Group > /LMATRIX = "G1" ALL 1 1 0 0 0 > /LMATRIX = "G1" ALL 1 0 1 0 0 > /LMATRIX = "G1" ALL 1 0 0 1 0 > /LMATRIX = "G1" ALL 1 0 0 0 1 > . > > * Use MEANS to verify that the group means are correct. > > means Y by group. > > ****** End of demo ****** . > > Ryan, are those LMATRIX commands including "int" working for you? Based on > what I've seen (and perusal of the FM), I /think/ they might have to be > changed to: > > /lmatrix = 'a1b1' ALL 1 1 0 0 1 0 1 0 0 0 0 0 > /lmatrix = 'a1b2' ALL 1 1 0 0 0 1 0 1 0 0 0 0 > /lmatrix = 'a2b1' ALL 1 0 1 0 1 0 0 0 1 0 0 0 > /lmatrix = 'a2b2' ALL 1 0 1 0 0 1 0 0 0 1 0 0 > /lmatrix = 'a3b1' ALL 1 0 0 1 1 0 0 0 0 0 1 0 > /lmatrix = 'a3b2' ALL 1 0 0 1 0 1 0 0 0 0 0 1 > > Thanks for clarifying. > Bruce > > > > R B wrote >> >> Kelly, >> >> A 3X2 design can be depicted as follows: >> >> Factor B >> 1 2 >> --------- >> 1 |a1b1|a1b2| >> Factor A 2 |a2b1|a2b2| >> 3 |a3b1|a3b2| >> --------- >> >> With that said, the following LMATRIX statements estimate the cell means: >> >> /lmatrix = 'a1b1' int 1 a 1 0 0 b 1 0 a*b 1 0 0 0 0 0 >> /lmatrix = 'a1b2' int 1 a 1 0 0 b 0 1 a*b 0 1 0 0 0 0 >> /lmatrix = 'a2b1' int 1 a 0 1 0 b 1 0 a*b 0 0 1 0 0 0 >> /lmatrix = 'a2b2' int 1 a 0 1 0 b 0 1 a*b 0 0 0 1 0 0 >> /lmatrix = 'a3b1' int 1 a 0 0 1 b 1 0 a*b 0 0 0 0 1 0 >> /lmatrix = 'a3b2' int 1 a 0 0 1 b 0 1 a*b 0 0 0 0 0 1 >> >> --- snip --- >> >> > > > ----- > -- > Bruce Weaver > [hidden email] > http://sites.google.com/a/lakeheadu.ca/bweaver/ > > "When all else fails, RTFM." > > NOTE: My Hotmail account is not monitored regularly. > To send me an e-mail, please use the address shown above. > > -- > View this message in context: http://spssx-discussion.1045642.n5.nabble.com/Polynomial-contrast-for-interaction-in-completely-between-Ss-design-tp4941355p5550813.html > Sent from the SPSSX Discussion mailing list archive at Nabble.com. > > ===================== > To manage your subscription to SPSSX-L, send a message to > [hidden email] (not to SPSSX-L), with no body text except the > command. To leave the list, send the command > SIGNOFF SPSSX-L > For a list of commands to manage subscriptions, send the command > INFO REFCARD ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
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I suspected you were doing something that worked for MIXED. ;-) Thanks for clarifying.
By the way, I do like your suggestion of starting by estimating the means, and then subtracting one vector from another to get any contrasts of interest. I think that must help reduce the likelihood of specifying a contrast incorrectly. Cheers, Bruce
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Bruce Weaver bweaver@lakeheadu.ca http://sites.google.com/a/lakeheadu.ca/bweaver/ "When all else fails, RTFM." PLEASE NOTE THE FOLLOWING: 1. My Hotmail account is not monitored regularly. To send me an e-mail, please use the address shown above. 2. The SPSSX Discussion forum on Nabble is no longer linked to the SPSSX-L listserv administered by UGA (https://listserv.uga.edu/). |
Hi,
Situation Currently, my company is looking at reducing a set of scale type Key Performance Indicators (KPIs) and these different KPIs are arranged into different segment namely Satisfaction (v1 to v12), efficiently (v1 to v5), etc, etc. The reason why they want to reduce is because there are over 100 KPIs... Methodology used The most immediate solution which I could think of is Factor Analysis using (PCA) Varimax Rotation, based on the individual segment since I am to reduced these 100 scale variables. Problem Faced I have 2 questions namely: 1) Am I heading the right direction in this analysis by using Factor analysis using (PCA) Varimax Rotation? 2) I am also looking at applying the Factor analysis on all the variables to check across the segments based on 2 methods. Please let me know of the implications if any for the 2 methods: a) Applying Factor analysis (PCA) Varimax Rotation on all the 100 variables. b) Applying Factor analysis again on the PCA components churned out by the individual segements. 3) In this analysis, there is no dependent variable so I could not use a linear model to measure the importance of all these 100 variables. My management would like to find out if we could measure the importance without the presence of a dependent variable. I would like to know if the extraction could give a hint on which variable is important to Satisfaction (Example : v6, v9 and v11 are the top 3 most important variables for the management to handle should they want to improve Satisfaction).
Any advise would be great. Thanks. Dorraj Oet. |
From your example --You are starting with a dozen or 20
different segments that you already have names for, such as Satisfaction. The obvious starting point for data that looks like this is to define the separate "scales" like satisfaction, probably as simple item-averages, and look at the relationship among those scales. If you want to say something about the items within the scales, SPSS has available the Reliability procedure. - I would expect, for instance -- the items with low communalities will look the least helpful, according to the criteria available in Reliabilities... Reliabilities does give you several criteria, in place of just "communalities", to look at the internal consistency. All things being equal, psychometricians will prefer a longer scale over a shorter scale, because the longer scales has a better reliability. But a particular added item may result in a smaller coefficient alpha (Cronbach's alpha), showing that it should be omitted. Please keep in mind that the "importance" that you can derive from staring only at a set of related variables does not reflect Importance for some other criterion; it is limited to reporting "what they have in common". A low contribution for one item could be an indication that you need *more* items like that one to make a better "universe of items"; and not that you should drop the item. (Example: If "satisfaction" has two components, physical and mental, and your set of items has 6 of one and 1 of the other, the single item will increase the internal reliability. Dropping it will decrease the *validity* of the broad concept, even while raising its measure of internal consistency.) The same principle applies to your overall factor analysis of scales, too. That is -- the principal component shows what is most common across the whole set of items. That is "most important" only when the full universe of items is a set that is balanced and well-measured. You get from a factor analysis a summary of what you put in it. -- Rich Ulrich Date: Mon, 12 Mar 2012 06:30:18 +0000 From: [hidden email] Subject: Factor Analysis To: [hidden email]
Hi, Situation Currently, my company is looking at reducing a set of scale type Key Performance Indicators (KPIs) and these different KPIs are arranged into different segment namely Satisfaction (v1 to v12), efficiently (v1 to v5), etc, etc. The reason why they want to reduce is because there are over 100 KPIs... Methodology used The most immediate solution which I could think of is Factor Analysis using (PCA) Varimax Rotation, based on the individual segment since I am to reduced these 100 scale variables. Problem Faced I have 2 questions namely: 1) Am I heading the right direction in this analysis by using Factor analysis using (PCA) Varimax Rotation? 2) I am also looking at applying the Factor analysis on all the variables to check across the segments based on 2 methods. Please let me know of the implications if any for the 2 methods: a) Applying Factor analysis (PCA) Varimax Rotation on all the 100 variables. b) Applying Factor analysis again on the PCA components churned out by the individual segements. 3) In this analysis, there is no dependent variable so I could not use a linear model to measure the importance of all these 100 variables. My management would like to find out if we could measure the importance without the presence of a dependent variable. I would like to know if the extraction could give a hint on which variable is important to Satisfaction (Example : v6, v9 and v11 are the top 3 most important variables for the management to handle should they want to improve Satisfaction).
Any advise would be great. Thanks. Dorraj Oet. |
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In reply to this post by Ryan
In October of 2011, I posted a message demonstrating how to construct a linear trend contrast using the TEST sub-command in MIXED (link below). The linear trend contrast was correct, but when I explained how to estimate the group-specifc slopes (a=1, a=2), I made a couple of mistatements.
First, the DIVISOR actually needed to be:
= sum[(ci)^2] = (-3)^2 + (-1)^2 + (1)^2 + (3)^2 = 9 + 1 + 9 + 1 = 20 assuming that the row spacing was 1. Not sure why I stated 10 in that post--I was probably thinking about a linear trend with 5 coefficients: -2 -1 0 1 2.
Second, to estimate the group-specific slopes using linear regression the coefficients would be treated as a continuous IV and the group-specific means would be the DV. Best, Ryan On Sat, Oct 29, 2011 at 12:11 PM, R B <[hidden email]> wrote: You should be able to view my post formatted correctly here: I can't believe it's been so long since that post. Time flies when you're |
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