Databases
StackOverflow2013
Postsdbo
POResults from TukeyHSD in R
 

Note that there are some explanatory texts on larger screens.

plurals
  1. POResults from TukeyHSD in R
    primarykey
    data
    text
    <p>I found one similar question here but i think my problem is if i interpret my data right.</p> <p>I do my simple anova and found that in my data i have an significant different (p.value &lt; 0.05:</p> <pre><code>an&lt;-aov(Value ~ Group, data=mydata) </code></pre> <p>Then i do my TukeyHSD:</p> <pre><code>TukeyHSD(an) </code></pre> <p>and my output looks like that:</p> <pre><code>Tukey multiple comparisons of means 95% family-wise confidence level Fit: aov(formula = Value ~ Group, data = kwdata) diff lwr upr p adj X-A -3.15668041 -8.0916672 1.7783064 0.6646288 C-A -2.07921381 -5.0632490 0.9048214 0.5209910 D-A 0.54997509 -1.8916800 2.9916302 0.9999804 w-X 3.79964159 -3.6284972 11.2277804 0.9108728 D-C 2.62918890 -0.5801339 5.8385117 0.2473717 </code></pre> <p>If i unterstand it right the combination of my groups with the lwr-value which is over 0.0 is the group which has the highest significant difference. Is this right?</p> <p>I am not sure how i could detect the groups which has a significant difference from the tukeyhsd.</p> <p>This output are only a few lines from the real output. My task is to analyse multi groups and to detect the groups which has the significant difference.</p> <p>Edit:</p> <p>Now an complete example:</p> <pre><code>Value&lt;- c(-0.9944999814033508,-0.35850000381469727,0.7063000202178955,-1.774399995803833,-1.080299973487854,0.30550000071525574,1.8499999046325684,-0.4124999940395355,0.5827999711036682,1.7506999969482422,-6.693999767303467,-0.8779000043869019,-1.3408000469207764,1.2560999393463135,-0.10040000081062317,1.8499999046325684,-0.3319000005722046,0.4957999885082245,0.8779000043869019,0.7387999892234802,0.8779000043869019,0.9154000282287598,0.8779000043869019,0.7063000202178955,-1.3408000469207764,0.7063000202178955,-0.3319000005722046,-1.6448999643325806,0.4124999940395355,-1.6448999643325806,-0.8779000043869019,0.7487000226974487,0.4399000108242035,1.8499999046325684,-1.6448999643325806,-2.4323999881744385,1.2265000343322754,-0.4957999885082245,-9.999899864196777,-1.7506999969482422,-1.6448999643325806,-9.999899864196777,0.8779000043869019,-5.06279993057251,0.8779000043869019,-2.9677000045776367,-5.06279993057251,-6.693999767303467,-1.0990500450134277,0.9944999814033508,-0.4677000045776367,-0.35850000381469727,-9.999899864196777,0.5827999711036682,0.7487000226974487,0.7387999892234802,-0.2533000111579895,-9.999899864196777,-1.0363999605178833,0.30550000071525574,-1.1749999523162842,-0.8064000010490417,-9.999899864196777,-0.9944999814033508,-2.478300094604492,-0.1509999930858612,0.4957999885082245,-4.571800231933594,-6.324900150299072,-0.38530001044273376,-1.3408000469207764,-5.93179988861084,-6.693999767303467,-2.9677000045776367,0.8779000043869019,-0.050200000405311584,-1.774399995803833,-0.1509999930858612,-0.23725003004074097,-0.6432999968528748,1.2560999393463135,-0.10040000081062317,0.4399000108242035,-0.7063000202178955,0.9154000282287598,-0.21819999814033508,1.2265000343322754,-0.4124999940395355,0.17640000581741333,-1.4758000373840332,-0.9944999814033508,-1.080299973487854,-0.6432999968528748,-9.999899864196777,-2.0536999702453613,-0.21819999814033508,0.7487000226974487,0.025100000202655792,-1.0363999605178833,-0.050200000405311584,-0.7387999892234802,0.4957999885082245,-1.4758000373840332,-0.7063000202178955,0.17640000581741333,-5.06279993057251,-0.6432999968528748,-1.4758000373840332,-0.9944999814033508,-0.2533000111579895,0.17640000581741333,-0.3319000005722046,0.6776500344276428,0.30550000071525574,-0.050200000405311584,0.5827999711036682,1.2560999393463135,-0.4957999885082245,-0.38530001044273376,0.9944999814033508,-2.4323999881744385,1.1263999938964844,-0.9944999814033508,1.7506999969482422,1.080299973487854,-0.7387999892234802,-1.3408000469207764,0.6128000020980835,-2.0536999702453613,0.7063000202178955,-0.8064000010490417,-0.8779000043869019,-0.050200000405311584,-2.9677000045776367,-0.8779000043869019,-2.0536999702453613,-1.3408000469207764,-1.3408000469207764,-0.38530001044273376,0.7063000202178955,-9.999899864196777,-0.4677000045776367,0.7721999883651733,0.025100000202655792,1.1263999938964844,-6.324900150299072,-0.1509999930858612,-0.4399000108242035,-0.9944999814033508,-0.9944999814033508,-0.4677000045776367,-1.0363999605178833,-1.7506999969482422,1.2265000343322754,-0.8779000043869019,0.6128000020980835,-0.050200000405311584,0.5827999711036682,-0.7063000202178955,-0.6432999968528748,-0.23725003004074097,0.025100000202655792,0.4124999940395355,0.7721999883651733,-1.0990500450134277) Value&lt;-c(Value,0.9944999814033508,-0.2533000111579895,1.2560999393463135,-0.21819999814033508,-1.1749999523162842,-0.38530001044273376,-0.4399000108242035,-0.7063000202178955,-2.478300094604492,-2.4323999881744385,0.9154000282287598,-0.23725003004074097,-0.38530001044273376,-1.6448999643325806,-0.050200000405311584,1.8499999046325684,-0.38530001044273376,-0.6432999968528748,-4.571800231933594,-6.693999767303467,-1.7506999969482422,1.080299973487854,0.4124999940395355,-1.3408000469207764,-5.93179988861084,-0.35850000381469727,-0.6432999968528748,-0.4124999940395355,-1.0990500450134277,-0.9944999814033508,-0.8064000010490417) Group&lt;-factor(c(rep('D',18),rep('C',1),rep('A',7),rep('B',34),rep('E',3),rep('F',4),rep('G',10),rep('H',2),rep('I',29),rep('J',16),rep('N',1),rep('M',1),rep('Z',2),rep('X',67),rep('O',1))) mydata&lt;-data.frame(Group, Value) summary(aov(Value ~Group,mydata)) TukeyHSD(aov(Value ~Group)) </code></pre> <p>My questions are:</p> <ol> <li>How can i detect the significant difference? With the p adj column and if how?</li> <li>(Additional Questions) Can i execute Tukey and then execute pairwise.wilcoxon and get the cut-set of the groups which have a significant different. Is this a robuster way in the statistics?</li> </ol>
    singulars
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. PTQuestion
    1. USbladepit
    1. USbladepit
    plurals
    1. PL
      singulars
      1. LTLinked
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. COtry searching for "[r] tukeyhsd" on stackoverflow. I answered a question recently that should give you a good start. (By the way, picking out pairwise comparisons with significant effects and ignoring the rest is often bad statistical practice ...)
      singulars
      1. POResults from TukeyHSD in R
      1. USBen Bolker
    2. COok i think i have a big mistake in my task...i thought that i do pairwise comparisons....i've looked at an question here but it didnt help me...
      singulars
      1. POResults from TukeyHSD in R
      1. USbladepit
    3. COcan you please post a reproducible example? http://tinyurl.com/reproducible-000 . If you want you can copy the example from http://stackoverflow.com/questions/16470404/tukeyhsd-adjusted-p-value-is-0-0000000/16471613#16471613 , although you might want to use an example where there are some significant and some non-significant comparisons
      singulars
      1. POResults from TukeyHSD in R
      1. USBen Bolker
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload