DrMark
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Cheers EJ - hope all is well with you and the team in Amsterdam
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Just noted that it was mentioned in your Nov 2017 blog that was all. Mark
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Hi I believe that Wilcoxon first defined the test which was further adapted by Mann-Whitney - hence the analysis is often termed the Wilcoxon- Mann-Whitney test. I think R reports U as W which are essentially the same value. I am ready to stand co…
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Hi Julia This may help - it is a tutorial written for students covering this https://forum.cogsci.nl/uploads/101/79GCEZG1F0YX.pdf Cheers Mark
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Seems to work when removing the space and running last nights .msi Cheers Mark https://forum.cogsci.nl/uploads/235/DQKAVI99W3E4.png
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Here you go Koen https://forum.cogsci.nl/uploads/360/BBNL90CDQ7Z2.csv
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https://forum.cogsci.nl/uploads/717/SLGJV2YRJEFW.png Hi Koen Still doesn't like it :-( However if i leave the constraints box empty it does still give a default hypothesis result. Mark
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Thanks EJ
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Hi Koen - here it is https://forum.cogsci.nl/uploads/863/DPK7AAC14VTY.png
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Hi Stat_b The default output for linear regression is Model summary ANOVA Coefficients - with the intercept and unstandardised B values Mark
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Thanks EJ missed that one Mark
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Cheers Johnny
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If it helps - p=.005 in SPSS as well (Image)
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This video explains it I believe - from 2.10min onwards https://www.youtube.com/watch?v=UHgvalPpgZQ Cheers Mark
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Looks like this was raised in Nov 2016 on GitHub but nothing more since. Cheers Mark
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This is the method in SPSS (Image)
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Hi EJ - looking at data reduction in effect. Eg comparing brain size in males and females, combining data such as height, body mass etc into one column of data to use as a covariate factor
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BTW - we have just moved all our undergraduate and postgraduate teaching from SPSS (where students have to be dragged screaming by wild horses to lectures) to the much more intuitive JASP. The software is now available to all students through our U…
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Thanks - thats where I adapted it from. My colleague has suggested that the coefficients are used in a different way to the intercept and gradient given by the linear regression coefficients. In this case the outcome (y)is predicted where y = ({x - …
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Thanks for your reply - I just realised that the error was there only for 2x3 tables - Phi is only calculated for 2x2 tables. Sorry it was me having a very senior moment. Cheers Mark