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Date:         Mon, 7 Mar 2011 13:38:51 -0800
Reply-To:     Bruce Weaver <bruce.weaver@hotmail.com>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Bruce Weaver <bruce.weaver@hotmail.com>
Subject:      Re: Anova SS1 vSS3 (using v 17.0)
In-Reply-To:  <1299516429121-3412719.post@n5.nabble.com>
Content-Type: text/plain; charset=us-ascii

I've now had time to take another look at this. It seems to me that both Method (aka "assay") and Replicate are within-Ss (or repeated measures) factors, with 2 and 3 levels respectively. It is also clear that ALIQUOT is completely confounded with ID. If all of this is correct, then have a 2x3 repeated measures ANOVA, with repeated measures on both factors. To run that model in the usual fashion, you have to restructure the data from LONG to WIDE.

data list list / Row id (2f5.0) aliquot(a1) assay rep (2f2.0) kt lkt (2f8.2). begin data 151. 26 A 1 1 44.550 1.648848 152. 26 A 1 2 39.230 1.593615 153. 26 A 1 3 27.186 1.434345 154. 26 A 2 4 37.453 1.573482 155. 26 A 2 5 49.918 1.698259 156. 26 A 2 6 38.341 1.583661 169. 29 B 1 1 13.450 1.128722 170. 29 B 1 2 6.879 .8375258 171. 29 B 1 3 5.764 .7607239 172. 29 B 2 4 13.116 1.117787 173. 29 B 2 5 11.543 1.062301 174. 29 B 2 6 11.044 1.043127 181. 31 C 1 1 11.400 1.056905 182. 31 C 1 2 6.657 .8233027 183. 31 C 1 3 6.375 .8044802 184. 31 C 2 4 10.415 1.017641 185. 31 C 2 5 11.371 1.055816 186. 31 C 2 6 10.770 1.032208 199. 34 D 1 1 10.161 1.006936 200. 34 D 1 2 5.089 .7066036 201. 34 D 1 3 6.668 .8239956 202. 34 D 2 4 10.955 1.039603 203. 34 D 2 5 12.827 1.108116 204. 34 D 2 6 9.793 .9909264 211. 36 E 1 1 17.000 1.230449 212. 36 E 1 2 10.942 1.039088 213. 36 E 1 3 10.096 1.004149 214. 36 E 2 4 16.018 1.204596 215. 36 E 2 5 13.289 1.123484 216. 36 E 2 6 16.138 1.207857 end data.

* GLM Repeated Measures needs WIDE file format, so restructure.

CASESTOVARS /ID=id /INDEX=assay rep /DROP = row /GROUPBY=VARIABLE.

* Try model with ALIQUOT as a Between-Ss factor.

GLM lkt.1.1 lkt.1.2 lkt.1.3 lkt.2.4 lkt.2.5 lkt.2.6 BY aliquot /WSFACTOR=method 2 Polynomial rep 3 Polynomial /METHOD=SSTYPE(3) /EMMEANS=TABLES(aliquot) /EMMEANS=TABLES(method) /EMMEANS=TABLES(rep) /EMMEANS=TABLES(aliquot*method) /EMMEANS=TABLES(aliquot*rep) /EMMEANS=TABLES(method*rep) /EMMEANS=TABLES(aliquot*method*rep) /CRITERIA=ALPHA(.05) /WSDESIGN=method rep method*rep /DESIGN=aliquot.

* That model does not work, because ALIQUOT is completely * confounded with ID -- i.e., there is only one ID for * each level of ALIQUOT.

* Run the model without the Between-Ss factor ALIQUOT.

GLM lkt.1.1 lkt.1.2 lkt.1.3 lkt.2.4 lkt.2.5 lkt.2.6 /WSFACTOR=method 2 Polynomial rep 3 Polynomial /METHOD=SSTYPE(3) /PLOT=PROFILE(rep*method) /EMMEANS=TABLES(method) /EMMEANS=TABLES(rep) /EMMEANS=TABLES(method*rep) compare(rep) adj(bonferroni) /CRITERIA=ALPHA(.05) /WSDESIGN=method rep method*rep.

HTH.

Bruce Weaver wrote: > > Your UNIANOVA syntax lists "method" as one of the factors, but "method" is > not included in the description of the data. Are "assay" and "method" > referring to the same variable? > > Also, UNIANOVA treats the 6 replicates per ID as if they are independent > observations. But if they are repeated measures on the same unit (ID), > then they will not be completely independent of each other, and should be > treated accordingly. One way to do that is via a mixed design > (between-within, or split-plot) ANOVA (Analyze - GLM - Repeated Measures). > For this approach, you would have to restructure the data to have one row > per ID, with the 6 replicates appearing in 6 columns. (Look up > CASESTOVARS to see how to restructure the data.) > > HTH. > > > > Allan Reese (Cefas) wrote: >> >> I have a completely balanced dataset and fit the main effects only using >> default (type 3) sums of squares. It reports 0df and 0ss for a factor >> with two levels. Switching to type 1 sums of squares, it gives 1df and >> a sensible sum of squares. Is there a simple reason why sstype(3) >> should be so ornery? >> >> On a point of terminology, are SPSS hierarchical sums of squares >> identical to SAS sequential ss? >> >> Data: >> Row id aliquot assay rep kt lkt (the response) >> 151. 26 A 1 1 44.550 1.648848 >> 152. 26 A 1 2 39.230 1.593615 >> 153. 26 A 1 3 27.186 1.434345 >> 154. 26 A 2 4 37.453 1.573482 >> 155. 26 A 2 5 49.918 1.698259 >> 156. 26 A 2 6 38.341 1.583661 >> 169. 29 B 1 1 13.450 1.128722 >> 170. 29 B 1 2 6.879 .8375258 >> 171. 29 B 1 3 5.764 .7607239 >> 172. 29 B 2 4 13.116 1.117787 >> 173. 29 B 2 5 11.543 1.062301 >> 174. 29 B 2 6 11.044 1.043127 >> 181. 31 C 1 1 11.400 1.056905 >> 182. 31 C 1 2 6.657 .8233027 >> 183. 31 C 1 3 6.375 .8044802 >> 184. 31 C 2 4 10.415 1.017641 >> 185. 31 C 2 5 11.371 1.055816 >> 186. 31 C 2 6 10.770 1.032208 >> 199. 34 D 1 1 10.161 1.006936 >> 200. 34 D 1 2 5.089 .7066036 >> 201. 34 D 1 3 6.668 .8239956 >> 202. 34 D 2 4 10.955 1.039603 >> 203. 34 D 2 5 12.827 1.108116 >> 204. 34 D 2 6 9.793 .9909264 >> 211. 36 E 1 1 17.000 1.230449 >> 212. 36 E 1 2 10.942 1.039088 >> 213. 36 E 1 3 10.096 1.004149 >> 214. 36 E 2 4 16.018 1.204596 >> 215. 36 E 2 5 13.289 1.123484 >> 216. 36 E 2 6 16.138 1.207857 >> >> >> UNIANOVA lkt BY aliquot method replicate >> /METHOD=SSTYPE(1) >> /INTERCEPT=INCLUDE >> /EMMEANS=TABLES(method) >> /CRITERIA=ALPHA(.01) >> /DESIGN=method aliquot replicate. >> >> Univariate Analysis of Variance >> >> Notes >> |-------------------------------|---------------| >> |Output Created |07-Mar-2011 15:| >> | |25:24 | >> |-------------------------------|---------------| >> |Comments | | >> |---------------|---------------|---------------| >> |Input |Active Dataset |DataSet0 | >> | |---------------|---------------| >> | |Filter | | >> | |---------------|---------------| >> | |Weight | | >> | |---------------|---------------| >> | |Split File | | >> | |---------------|---------------| >> | |N of Rows in |30 | >> | |Working Data | | >> | |File | | >> |---------------|---------------|---------------| >> |Missing Value |Definition of |User-defined | >> |Handling |Missing |missing values | >> | | |are treated as | >> | | |missing. | >> | |---------------|---------------| >> | |Cases Used |Statistics are | >> | | |based on all | >> | | |cases with | >> | | |valid data for | >> | | |all variables | >> | | |in the model. | >> |---------------|---------------|---------------| >> |Syntax |UNIANOVA lkt | >> | |BY aliquot | >> | |method | >> | |replicate | >> | |/METHOD=SSTYPE | >> | |(1) | >> | |/INTERCEPT=INCL| >> | |UDE | >> | |/EMMEANS=TABLES| >> | |(method) | >> | | | >> | |/CRITERIA=ALPHA| >> | |(.01) | >> | | | >> | |/DESIGN=method | >> |---------------|---------------|---------------| >> |Resources |Processor Time |0:00:00.016 | >> | |---------------|---------------| >> | |Elapsed Time |0:00:00.031 | >> |---------------|---------------|---------------| >> >> >> >> [DataSet0] >> >> >> Between-Subjects Factors >> |--------------|--| >> | |N | >> |---------|----|--| >> |aliquot |A |6 | >> | |----|--| >> | |B |6 | >> | |----|--| >> | |C |6 | >> | |----|--| >> | |D |6 | >> | |----|--| >> | |E |6 | >> |---------|----|--| >> |method |1.00|15| >> | |----|--| >> | |2.00|15| >> |---------|----|--| >> |replicate|1.00|5 | >> | |----|--| >> | |2.00|5 | >> | |----|--| >> | |3.00|5 | >> | |----|--| >> | |4.00|5 | >> | |----|--| >> | |5.00|5 | >> | |----|--| >> | |6.00|5 | >> |---------|----|--| >> >> >> >> Tests of Between-Subjects Effects >> Dependent Variable:lkt >> |---------------|---------------|--|-----------|---------|----| >> |Source |Type I Sum of |df|Mean Square|F |Sig.| >> | |Squares | | | | | >> |---------------|---------------|--|-----------|---------|----| >> |Corrected Model|2.056a |9 |.228 |61.462 |.000| >> |---------------|---------------|--|-----------|---------|----| >> |Intercept |37.988 |1 |37.988 |10219.052|.000| >> |---------------|---------------|--|-----------|---------|----| >> |method |.128 |1 |.128 |34.418 |.000| >> |---------------|---------------|--|-----------|---------|----| >> |aliquot |1.743 |4 |.436 |117.219 |.000| >> |---------------|---------------|--|-----------|---------|----| >> |replicate |.185 |4 |.046 |12.466 |.000| >> |---------------|---------------|--|-----------|---------|----| >> |Error |.074 |20|.004 | | | >> |---------------|---------------|--|-----------|---------|----| >> |Total |40.119 |30| | | | >> |---------------|---------------|--|-----------|---------|----| >> |Corrected Total|2.131 |29| | | | >> |---------------|---------------|--|-----------|---------|----| >> a. R Squared = .965 (Adjusted R Squared = .949) >> >> [method+aliquot+replicate ss sum to model ss] >> >> >> Estimated Marginal Means >> >> method >> Dependent Variable:lkt >> |------|----|----------|---------------------------| >> |method|Mean|Std. Error|99% Confidence Interval | >> | | | | | >> | | | |---------------|-----------| >> | | | |Lower Bound |Upper Bound| >> |------|----|----------|---------------|-----------| >> |1.00 |.a |. |. |. | >> |------|----|----------|---------------|-----------| >> |2.00 |.a |. |. |. | >> |------|----|----------|---------------|-----------| >> a. This modified population marginal mean is not estimable. >> >> >> >> UNIANOVA lkt BY aliquot method replicate >> /METHOD=SSTYPE(3) >> /INTERCEPT=INCLUDE >> /EMMEANS=TABLES(method) >> /CRITERIA=ALPHA(.01) >> /DESIGN=method aliquot replicate. >> >> >> >> >> Tests of Between-Subjects Effects >> Dependent Variable:lkt >> |---------------|---------------|--|-----------|---------|----| >> |Source |Type III Sum |df|Mean Square|F |Sig.| >> | |of Squares | | | | | >> |---------------|---------------|--|-----------|---------|----| >> |Corrected Model|2.056a |9 |.228 |61.462 |.000| >> |---------------|---------------|--|-----------|---------|----| >> |Intercept |37.988 |1 |37.988 |10219.052|.000| >> |---------------|---------------|--|-----------|---------|----| >> |method |.000 |0 |. |. |. | >> |---------------|---------------|--|-----------|---------|----| >> |aliquot |1.743 |4 |.436 |117.219 |.000| >> |---------------|---------------|--|-----------|---------|----| >> |replicate |.185 |4 |.046 |12.466 |.000| >> |---------------|---------------|--|-----------|---------|----| >> |Error |.074 |20|.004 | | | >> |---------------|---------------|--|-----------|---------|----| >> |Total |40.119 |30| | | | >> |---------------|---------------|--|-----------|---------|----| >> |Corrected Total|2.131 |29| | | | >> |---------------|---------------|--|-----------|---------|----| >> a. R Squared = .965 (Adjusted R Squared = .949) >> >> >> >> Estimated Marginal Means >> >> method >> Dependent Variable:lkt >> |------|----|----------|---------------------------| >> |method|Mean|Std. Error|99% Confidence Interval | >> | | | | | >> | | | |---------------|-----------| >> | | | |Lower Bound |Upper Bound| >> |------|----|----------|---------------|-----------| >> |1.00 |.a |. |. |. | >> |------|----|----------|---------------|-----------| >> |2.00 |.a |. |. |. | >> |------|----|----------|---------------|-----------| >> a. This modified population marginal mean is not estimable. >> >> [model ss does not equal sum of parts] >> >> >> Thanks for any comments >> Allan >> >> >> >> >> >> R Allan Reese >> Senior statistician, Cefas >> The Nothe, Weymouth DT4 8UB >> >> Tel: +44 (0)1305 206614 -direct >> Fax: +44 (0)1305 206601 >> >> www.cefas.co.uk >> *********************************************************************************** >> >> This email and any attachments are intended for the named recipient only. >> Its unauthorised use, distribution, disclosure, storage or copying is not >> permitted. If you have received it in error, please destroy all copies >> and notify the sender. In messages of a non-business nature, the views >> and opinions expressed are the author's own and do not necessarily >> reflect those of the organisation from which it is sent. All emails may >> be subject to monitoring. >> >> *********************************************************************************** >> >

----- -- Bruce Weaver bweaver@lakeheadu.ca 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.

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