Hi Donna, Thanks for your quick reply. so that means that the clusters I see when I load T-Map*TMapClusters.metric are all clusters in the real T-Map file that exceed my T-threshold, which means that their significance is not corrected for mulitple comparisons, right?
Thanks again, Julia > Hi Julia, > > Again, it has been years since I have used the cluster-based test, > having switched to TFCE. I'd probably have to dig around to find an old > dataset like that. > > But from what I remember, there was a tmap*metric that had a column with > the unthresholded t-map, but then there was also a tmap*Clusters*metric > that zeroed out everything that wasn't in a significant cluster. Based > on your filename, I'd guess that was the > latter type, so should have everything NOT in a significant cluster > zeroed out. If not, I'd wonder whether you have some underlay or > secondary overlay that is set to a different column/metric. > > At any rate, worst case, you can use Surface: ROI to threshold the > metric at -2.66 and select only nodes connected to the currently > selected node (where you ID a node inside the significant cluster). > > Donna > > On 12/01/2010 01:07 PM, Julia Bender wrote: >> Hi Donna, >> >> thanks for updating the code. I've rerun my stats with different >> thresholds (T=2.66, p.05). My *_SignificantClusters.txt file tells me >> that >> there is only one significant cluster: >> >> TMap >> ---- >> Column Thresh Num-Nodes Area Area-Corrected COG-X >> COG-Y COG-Z P-Value >> 1 -2.660 4203 2775.767090 2827.737549 40.409 >> -12.974 -27.389 0.002000 >> >> but when I load the T-Map*TMapClusters.metric file onto my surface I can >> see several clusters. Are those the uncorrected significant clusters? >> TMap >> ---- >> Column Thresh Num-Nodes Area Area-Corrected COG-X >> COG-Y COG-Z P-Value >> 1 -2.660 4203 2775.767090 2827.737549 40.409 >> -12.974 -27.389 0.002000 >> 1 2.660 435 219.168182 220.613358 28.160 >> -52.169 56.452 0.258000 >> 1 2.660 184 153.448578 158.166473 44.849 >> -24.530 49.967 0.365000 >> 1 2.660 229 153.459183 149.640244 35.705 >> -20.871 50.301 0.394000 >> 1 2.660 153 106.938622 107.896500 45.769 >> -0.412 39.610 0.541000 >> 1 2.660 142 90.582855 88.234703 27.666 >> -23.322 -13.406 0.641000 >> 1 2.660 143 81.723625 80.440567 49.349 >> -24.353 -2.452 0.683000 >> 1 2.660 181 67.850945 68.252045 19.675 >> -10.697 58.506 0.755000 >> 1 2.660 151 70.042465 67.372482 38.421 >> -37.124 46.450 0.757000 >> 1 -2.660 48 58.272926 59.562595 7.732 >> 17.195 -16.283 0.804000 >> 1 2.660 59 57.713173 56.583248 38.887 >> 13.286 33.244 0.821000 >> 1 -2.660 43 40.167896 41.627560 29.441 >> -80.470 -15.188 0.898000 >> 1 2.660 70 31.806927 31.897322 21.620 >> -64.665 49.982 0.937000 >> 1 2.660 57 29.297220 30.987967 5.613 >> -8.313 65.568 0.941000 >> 1 2.660 43 27.218239 26.574488 16.105 >> 30.667 49.513 0.960000 >> 1 2.660 31 14.005635 13.789747 37.211 >> -5.401 -5.390 0.993000 >> 1 2.660 21 12.719942 12.593773 50.215 >> -25.851 41.114 0.994000 >> 1 2.660 13 10.736663 10.448134 23.142 >> 39.879 31.981 0.997000 >> 1 2.660 9 5.134305 5.243526 17.070 >> -60.562 62.295 0.999000 >> 1 2.660 2 1.532340 1.510908 23.168 >> -34.540 -5.696 0.998000 >> >> It looks like it. >> >> Is there a way to display only the corrected significant clusters? >> >> Thanks a lot for your help, >> >> Julia >> >> >>> All of the statistical tests have been corrected so they should now >>> produce the correct P-Value. >>> >>> An updated caret distribution, v5.616, is now available for download >>> from >>> http://brainvis.wustl.edu/wiki/index.php/Caret:Download >>> (username=Rabbit >>> password=Carrot). >>> >>> The effect is generally very minimal (2/iterations -- .0004 using our >>> typical 5k). >>> >>> On 11/08/2010 09:18 AM, Donna Dierker wrote: >>> >>>> Julia, >>>> >>>> I see what you mean. Based on the report you uploaded, the p-values >>>> listed here seem off by .002: >>>> >>>> 1 2.500 1712 1229.060425 1242.687012 -27.858 >>>> -75.308 -13.617 0.036000 >>>> 1 2.500 1960 1059.480713 1062.812378 -21.474 >>>> -62.266 50.506 0.044000 >>>> >>>> I'll ask John about it. >>>> >>>> Donna >>>> >>>> On 11/08/2010 04:07 AM, Julia Bender wrote: >>>> >>>>> Hi Donna, >>>>> >>>>> thanks for your answers. I've uploaded >>>>> "T-Map_LH_cCue_EndoLeft.metric_TMap_Significant_Clusters.txt" which >>>>> is the >>>>> example file we've been talking about. As far as I see it the cluster >>>>> >>>>> TMap >>>>> ---- >>>>> Column Thresh Num-Nodes Area Area-Corrected >>>>> COG-X COG-Y COG-Z P-Value >>>>> 1 2.500 1712 1229.060425 1242.687012 -27.858 >>>>> -75.308 -13.617 0.036000 >>>>> >>>>> fits in between rank 37 (area corrected 1273.066772) and 38 >>>>> (area-corrected 1240.362915). >>>>> >>>>> Thanks for your help, >>>>> >>>>> Julia >>>>> >>>>> >>>>> >>>>> >>>>> >>>>>> On 11/04/2010 09:57 AM, Julia Bender wrote: >>>>>> >>>>>> >>>>>>> Hi Donna, >>>>>>> >>>>>>> thank you so much for your detailed reply. It helped a great deal. >>>>>>> Three things remain somewhat unclear to me: >>>>>>> >>>>>>> 1. I think I figured out why the list of permuted clusters in >>>>>>> xx.metric_TMap_Significant_Clusters.txt only has 696 instead of >>>>>>> 1000 >>>>>>> (=number of iterations) columns in the example contrast. My input >>>>>>> columns >>>>>>> were n=13, which would allow up to 2^13=8192 iterations. But only >>>>>>> 696 of >>>>>>> the 1000 iterations produce clusters with a T-Value above my >>>>>>> defined >>>>>>> threshold. Theses are the ones listed in the output file. Is that >>>>>>> possible? >>>>>>> >>>>>>> >>>>>>> >>>>>> Sure, it certainly is possible for the data to not survive >>>>>> threshold, >>>>>> but I'm not used to it. >>>>>> >>>>>> >>>>>>> 2. The significant cluster in the example has an area-corrected >>>>>>> value of >>>>>>> 1242.687012 and is assigned a p-value of 0.036. This means that it >>>>>>> resides >>>>>>> on rank 36 out of my 1000 iterations, right? When I looked up the >>>>>>> 100 >>>>>>> largest clusters list (my predefined P-threshold was .1) in my >>>>>>> output >>>>>>> file >>>>>>> the significant cluster would actually take rank 38. what am I >>>>>>> getting >>>>>>> wrong here? >>>>>>> >>>>>>> >>>>>>> >>>>>> Keep in mind that the p-values are based on the distribution built >>>>>> by >>>>>> the random tmaps, but the area of clusters on the real tmap is >>>>>> typically >>>>>> in between two areas on the randomized list. >>>>>> >>>>>> If your real tmap cluster is bigger than the 38th biggest random >>>>>> cluster, but smaller than the 37th, then I'd expect it to have a >>>>>> p-value >>>>>> of 38/iterations. >>>>>> >>>>>> If this is not happening, I don't know why. Upload your >>>>>> significance >>>>>> report, and I'll have a look: >>>>>> >>>>>> http://pulvinar.wustl.edu/cgi-bin/upload.cgi >>>>>> >>>>>> >>>>>>> 3.The correction for multiple comparisons is done by thresholding >>>>>>> all >>>>>>> real >>>>>>> T-map clusters above the predefined T-Value with the smallest >>>>>>> iterations*alpha cluster of the permutation distribution according >>>>>>> to >>>>>>> area-corrected? The corrected P-value for real T-map clusters that >>>>>>> survive >>>>>>> this threshold is derived from the rank the clusters hold in the >>>>>>> total >>>>>>> iterations list according to area-corrected? >>>>>>> >>>>>>> >>>>>>> >>>>>> I would put it differently. Any clusters in the real tmap surviving >>>>>> the >>>>>> threshold that exceed the minimum significance cut-off in corrected >>>>>> area >>>>>> are significant. >>>>>> >>>>>> >>>>>>> Again, thanks a lot for your answers!! >>>>>>> >>>>>>> Julia >>>>>>> >>>>>>> >>>>>>> >>>>>>> >>>>>>>> Hi Julia, >>>>>>>> >>>>>>>> Bear with me, because it's been years since I used the >>>>>>>> caret_command >>>>>>>> tests, which are mostly cluster tests. We switched from cluster >>>>>>>> to >>>>>>>> TFCE >>>>>>>> a year or so ago: >>>>>>>> >>>>>>>> http://brainvis.wustl.edu/wiki/index.php/Caret:Documentation:Statistics#Threshold-Free_Cluster_Enhancement_.28TFCE.29 >>>>>>>> >>>>>>>> >>>>>>>> But those tests are in caret_stats, which is a separate >>>>>>>> tool/package >>>>>>>> based on java. Let me know if you want to know more about that. >>>>>>>> >>>>>>>> My inline replies below reflect my best recollection of the >>>>>>>> cluster >>>>>>>> tests. >>>>>>>> >>>>>>>> Donna >>>>>>>> >>>>>>>> On 10/08/2010 08:16 AM, Julia Bender wrote: >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> Hi Donna, >>>>>>>>> >>>>>>>>> I've looked more into the "caret_command >>>>>>>>> -metric-statistics-one-sample-t-test" output files. I'm having >>>>>>>>> trouble >>>>>>>>> understanding what all the information means. Maybe you can >>>>>>>>> correct >>>>>>>>> me: >>>>>>>>> >>>>>>>>> 1. xx.metric_TMap.metric: >>>>>>>>> Map of T-Values for the wholebrain (?) for the contrast defined >>>>>>>>> in the >>>>>>>>> xx.metric input files. Those are T-Values exceeding the T-Value >>>>>>>>> thresholds >>>>>>>>> and alpha level I specified in >>>>>>>>> "caret_command-metric-statistics-one-sample-t-test" (eg -300000 >>>>>>>>> 2.5 >>>>>>>>> 0.1 >>>>>>>>> in >>>>>>>>> my case). >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> They are not thresholded. The 2.5 and 0.1 affect the cluster >>>>>>>> size, >>>>>>>> which affects downstream outputs. But this TMap is unthresholded. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> They are not corrected for multiple comparisons(?). >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> No, definitely not. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> This is the one I should load onto my surface. When I load >>>>>>>>> that TMap, why can I still see T-Values below my defined >>>>>>>>> threshold? >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> Right. I like to use the unthresholded t/f-map for my figures, >>>>>>>> but >>>>>>>> generate a border around the clusters that were significant, and >>>>>>>> show >>>>>>>> the border overlaid on the unthresholded t-map. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> 2.xx.metric_ShuffledTMap.metric: >>>>>>>>> Distribution of T-Values derived from permuting + and - on each >>>>>>>>> element >>>>>>>>> in >>>>>>>>> xx in N iterations (in my case 1000) >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> Right, and less than 1000, depending on how many columns there are >>>>>>>> in >>>>>>>> your input composite metric. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> 3.xx.metric_TMap_Significant_Clusters.txt: >>>>>>>>> This is what the help page says: >>>>>>>>> "1. Find the biggest cluster in each column of the permutation >>>>>>>>> T-Map >>>>>>>>> metric/shape file and sort them by cluster size." >>>>>>>>> I see two lists of clusters in the output file. I assume the one >>>>>>>>> that >>>>>>>>> is >>>>>>>>> the result of this sorting is the lower one. It has about 700 >>>>>>>>> rows >>>>>>>>> depending on xx, why does it not have 1000 rows, one for each >>>>>>>>> permutation? >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> See Sample Report: Two Sample T-Test here: >>>>>>>> >>>>>>>> http://brainvis.wustl.edu/OLD/courses/stats_neurosci/2008_BMEcourse/BME_dld_talk.htm >>>>>>>> >>>>>>>> >>>>>>>> Yours is a one-sample t-test, but I think the cluster lists will >>>>>>>> be the >>>>>>>> same. >>>>>>>> >>>>>>>> If your last list of clusters has less than 1000 rows, then you >>>>>>>> had >>>>>>>> fewer than 10 columns in your input composite metric. If n is the >>>>>>>> number of columns, and 2 raised to the n is less than your input >>>>>>>> iterations, then Caret will stop at 2^n. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> Are the clusters sorted by Num-Nodes, Area or Area corrected? >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> Descending area-corrected. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> In my files >>>>>>>>> they seem kind of sorted by both... How is a cluster defined? >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> By your input thresholds. The permuted t-maps are thresholded at >>>>>>>> the >>>>>>>> level specified, and then clusters of contiguous supra-threshold >>>>>>>> nodes >>>>>>>> are found. Only the largest in each iteration is saved. Then >>>>>>>> they are >>>>>>>> listed in descending order of area-corrected size. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> "2. Find the largest (alpha)(iterations) clusters in the >>>>>>>>> Permutation >>>>>>>>> T-Map >>>>>>>>> and use its cluster size as the Significant Cluster Cutoff." >>>>>>>>> I assume this is the list of T-Values right below the above list >>>>>>>>> of >>>>>>>>> clusters, why does it contain clusters with a P-Value that is >>>>>>>>> above my >>>>>>>>> defined alpha? >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> The last table lists all the largest clusters for each iteration, >>>>>>>> regardless of its p. The second table is what you want. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> "3. Find clusters in the Real T-Map file." This must be the upper >>>>>>>>> list >>>>>>>>> of >>>>>>>>> clusters (containing much less rows than the lower one) >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> Correct. That link above shows this the best. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> "4. Report all clusters in Real T-Map file that are larger than >>>>>>>>> Significant Cluster Cutoff." This is the list of T-Values below >>>>>>>>> this >>>>>>>>> list, >>>>>>>>> containing only clusters that are bigger than the cluster with >>>>>>>>> the >>>>>>>>> highest >>>>>>>>> P-Value found in 2. that pass the alpha and T-Value thresholds I >>>>>>>>> specified >>>>>>>>> in "caret_command-metric-statistics-one-sample-t-test". >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> Again, here is the relevant excerpt from the link above: >>>>>>>> >>>>>>>> Significant Area: 306.226 <--- area of smallest cluster listed >>>>>>>> in >>>>>>>> next >>>>>>>> section >>>>>>>> >>>>>>>> Shuffled TMap <--- Top alpha*iterations biggest clusters are >>>>>>>> listed >>>>>>>> below, >>>>>>>> in descending area-corrected sequence. >>>>>>>> (i.e., the smallest of which determines the signifiance area >>>>>>>> cut-off) >>>>>>>> ------------- >>>>>>>> Column Thresh Num-Nodes Area Area-Corrected >>>>>>>> COG-X >>>>>>>> COG-Y COG-Z P-Value >>>>>>>> 821 2.660 2300 1439.637207 1559.143188 >>>>>>>> -37.249 >>>>>>>> 0.007 -3.456 >>>>>>>> 150 2.660 792 598.519104 858.216492 >>>>>>>> -49.142 >>>>>>>> -32.369 11.918 >>>>>>>> 548 2.660 1380 641.563843 643.790466 >>>>>>>> -35.004 >>>>>>>> 2.519 -14.981 >>>>>>>> ... (middle biggest alpha*iterations entries omitted) >>>>>>>> 681 -2.660 279 249.739059 312.872681 >>>>>>>> -48.189 >>>>>>>> -9.576 10.352 >>>>>>>> 649 2.660 237 198.468857 311.602844 >>>>>>>> -16.170 >>>>>>>> -79.223 30.149 >>>>>>>> 633 -2.660 217 119.337837 306.226257 >>>>>>>> -42.479 >>>>>>>> -48.846 41.505 >>>>>>>> >>>>>>>> >>>>>>>> TMap <--- Significant real tmap clusters (i.e., >= significant >>>>>>>> area) >>>>>>>> are >>>>>>>> listed here; no entries here means no clusters were significant. >>>>>>>> ---- >>>>>>>> Column Thresh Num-Nodes Area Area-Corrected >>>>>>>> COG-X >>>>>>>> COG-Y COG-Z P-Value >>>>>>>> 3 2.660 344 229.353973 362.322113 >>>>>>>> -45.677 >>>>>>>> -27.442 18.039 0.029000 >>>>>>>> >>>>>>>> Shuffled TMap <--- All iterations max clusters are listed below, >>>>>>>> in >>>>>>>> descending area-corrected sequence. >>>>>>>> ------------- >>>>>>>> Column Thresh Num-Nodes Area Area-Corrected >>>>>>>> COG-X >>>>>>>> COG-Y COG-Z P-Value >>>>>>>> 821 2.660 2300 1439.637207 1559.143188 >>>>>>>> -37.249 >>>>>>>> 0.007 -3.456 >>>>>>>> 150 2.660 792 598.519104 858.216492 >>>>>>>> -49.142 >>>>>>>> -32.369 11.918 >>>>>>>> 548 2.660 1380 641.563843 643.790466 >>>>>>>> -35.004 >>>>>>>> 2.519 -14.981 >>>>>>>> ... (middle biggest alpha*iterations entries omitted) >>>>>>>> 3 2.660 1 0.475079 0.472114 >>>>>>>> -18.520 >>>>>>>> -24.418 -21.858 0.999000 >>>>>>>> 3 -2.660 1 0.474738 0.456814 >>>>>>>> -21.478 >>>>>>>> -36.579 -17.077 0.999000 >>>>>>>> 3 2.660 1 0.000000 0.000000 >>>>>>>> -6.822 >>>>>>>> -46.751 8.581 0.999000 >>>>>>>> >>>>>>>> ------------------------------------------------------------------------ >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> 4. T-Map_LH_cCue_EndoL_vs_Cue_ExoL.metric_TMapClusters.metric >>>>>>>>> Is this the map of clusters defined above? >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> This is what I believe you thought xx.metric_TMap.metric was, but >>>>>>>> it is >>>>>>>> unthresholded. >>>>>>>> >>>>>>>> This TMapClusters one zeroes out all nodes that are NOT within a >>>>>>>> significant cluster. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> I'm sorry, I know these are a many questions. Thanks a lot for >>>>>>>>> your >>>>>>>>> help! >>>>>>>>> >>>>>>>>> Julia >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> Julia, >>>>>>>>>> I looked at your report and your t-map, which is consistent with >>>>>>>>>> the >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> caret_command -metric-information output you included below. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> Just making sure you understand this part of the report: >>>>>>>>>> TMap >>>>>>>>>> ---- >>>>>>>>>> Column Thresh Num-Nodes Area Area-Corrected >>>>>>>>>> COG-X >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> COG-Y COG-Z P- >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> Value >>>>>>>>>> 1 2.500 3064 2223.228027 2245.943848 >>>>>>>>>> -30.317 >>>>>>>>>> -73.796 -12.228 0.0 >>>>>>>>>> 12000 >>>>>>>>>> 1 2.500 3372 1865.999878 1863.883423 >>>>>>>>>> -21.516 >>>>>>>>>> -62.842 46.382 0.0 >>>>>>>>>> 17000 >>>>>>>>>> 1 2.500 1557 681.308838 674.981384 >>>>>>>>>> -32.967 >>>>>>>>>> -5.873 48.701 0.0 >>>>>>>>>> 59000 >>>>>>>>>> These are the clusters in your real t-map that were significant >>>>>>>>>> at >>>>>>>>>> the >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> 0.1 >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> alpha you specified, using the 2.5 threshold. (Note that all >>>>>>>>>> the >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> significant clusters were at the positive end.) >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> I believe the reason you saw different max/min in the Caret GUI >>>>>>>>>> was >>>>>>>>>> that >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> you had the permuted t-map loaded, instead of the real one. In >>>>>>>>> your >>>>>>>>> message below, you said, "Adjustment:Column: permuted >>>>>>>>> T-Values,Threshold >>>>>>>>> type". There is nothing about permuted in the file you >>>>>>>>> uploaded. If >>>>>>>>> you >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> were viewing the permuted/shuffled t-map, this would also >>>>>>>>>> explain why >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> little would survive a low threshold. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> But we don't necessarily (or even usually) use the same values >>>>>>>>>> we >>>>>>>>>> used >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> for >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> cluster thresholds as the threshold for displaying t-maps, e.g., >>>>>>>>>> for >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> publication purposes. I think we like to see some color >>>>>>>>> differentiation >>>>>>>>> beyond the cluster threshold max. If they are the same, the >>>>>>>>> color >>>>>>>>> will >>>>>>>>> saturate at the max. Sometimes we'll use a p-value derived from >>>>>>>>> the >>>>>>>>> degrees of freedom and get a corresponding t-value from that, and >>>>>>>>> use >>>>>>>>> that >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> for thresholding. Other times we might just use, say, +/-4.0 or >>>>>>>>>> higher, >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> depending on how big the values get in the data. Usually we'll >>>>>>>>> use a >>>>>>>>> symmetric scale (i.e., -x to +x -- rather than different >>>>>>>>> min/max). >>>>>>>>> Donna >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> On 08/11/2010 09:12 AM, Julia Bender wrote: >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>> Hi Donna, >>>>>>>>>>> I've just uploaded the two files. >>>>>>>>>>> Thanks for your help! >>>>>>>>>>> Julia >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>>> Julia, >>>>>>>>>>>> It will be easier for me to get my head around your question >>>>>>>>>>>> if >>>>>>>>>>>> I >>>>>>>>>>>> can >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>> get two files: >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>> * T-Map_LH_cCue_Endo.metric_TMap.metric (whatever the final >>>>>>>>>>>> output >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>> metric was, but NOT the permuted/shuffled tmap file). >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>> * The report named something like *Signicance*.txt >>>>>>>>>>>> Could you upload those here: >>>>>>>>>>>> http://pulvinar.wustl.edu/cgi-bin/upload.cgi >>>>>>>>>>>> My brain would be ever so grateful. >>>>>>>>>>>> Donna >>>>>>>>>>>> On 08/11/2010 07:07 AM, Julia Bender wrote: >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>>> Hey everyone, >>>>>>>>>>>>> I'm a bit confused about how to threshold my T-Maps in >>>>>>>>>>>>> caret5. >>>>>>>>>>>>> I >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> created >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>>> the maps with the following command: >>>>>>>>>>>>> /usr/local/caret/bin_linux/caret_command >>>>>>>>>>>>> -metric-statistics-one-sample-t-test $EACHMETRIC >>>>>>>>>>>>> $FIDUCIAL_COORD >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> $OPEN_TOPO $SURFACE_SHAPE 3 T-Map_$EACHMETRIC -300000.0 2.5 0.10 >>>>>>>>> 10 1 >>>>>>>>> 1000 >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>>> 0 4 >>>>>>>>>>>>> So I put the negative threshold to -300000 and the positive >>>>>>>>>>>>> threshold >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> to >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>>> 2.5. When I look at the resulting Tmap.metric files it gives >>>>>>>>>>>>> me >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> something >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>>> like this: >>>>>>>>>>>>> Filename: T-Map_LH_cCue_Endo.metric_TMap.metric >>>>>>>>>>>>> Number of Nodes: 73730 >>>>>>>>>>>>> Number of Columns: 1 >>>>>>>>>>>>> Column Minimum Maximum Mean Sample >>>>>>>>>>>>> Dev >>>>>>>>>>>>> % >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> Positive % Negative Column Name >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>>> 1 -9.785 6.076 -0.950 >>>>>>>>>>>>> 2.639 >>>>>>>>>>>>> 36.234 63.766 T-Values >>>>>>>>>>>>> As far as I understand, this means the maximum negative T >>>>>>>>>>>>> value in >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> this >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>>> metric is -9.785 and the maximum positive T value is 6.076. >>>>>>>>>>>>> When I >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> open >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>>> the file in caret though (Color mapping: Auto Scale, Display >>>>>>>>>>>>> mode: >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> Both, >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>>> Display Color Bar, Threshold Adjustment:Column: permuted >>>>>>>>>>>>> T-Values,Threshold type: Column) the bar tells me that my >>>>>>>>>>>>> maximum >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> negative >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>>> value is -3.7 and my maximum positive value is 2.6. This also >>>>>>>>>>>>> holds >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> when >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>>> I >>>>>>>>>>>>> adjust the thresholds in the fields below to -2 and 2, when >>>>>>>>>>>>> almost >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> all >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>>>>> activation disappears. >>>>>>>>>>>>> Which is the correct information? >>>>>>>>>>>>> Thanks a lot for your help! >>>>>>>>>>>>> Julia >>>>>>>>>>>>> Dipl. Psych. Julia Bender >>>>>>>>>>>>> Humboldt Universität zu Berlin >>>>>>>>>>>>> Mathematisch - Naturwissenschaftliche Fakultät II >>>>>>>>>>>>> Institut für Psychologie, Abt. Klinische Psychologie >>>>>>>>>>>>> Unter den Linden 6 >>>>>>>>>>>>> D-10099 Berlin >>>>>>>>>>>>> > > _______________________________________________ > caret-users mailing list > [email protected] > http://brainvis.wustl.edu/mailman/listinfo/caret-users > Dipl. Psych. Julia Bender Humboldt Universit�t zu Berlin Mathematisch - Naturwissenschaftliche Fakult�t II Institut f�r Psychologie, Abt. Klinische Psychologie Unter den Linden 6 D-10099 Berlin _______________________________________________ caret-users mailing list [email protected] http://brainvis.wustl.edu/mailman/listinfo/caret-users
