Re: [R] U value from wilcox.test
Sorry that I did not answer you earlier, I would like to thank you again for your advice and the time you dedicated to my problem. In my case it was not possible to increase the sample size but I would take your advice into account for the next sampling and also for presenting these results! Thanks again, have a nice day! Best wishes, Chloé Le 21/08/2010 16:18, Cedric Laczny [via R] a écrit : Glad that I could help :) Another thing that came to my mind ist that when you simply look at the values of the different groups, they differ quite strongly in my opinion. They are between two and three times higher in the second group than the ones from the first group. Therefore it would be a good idea to increase your sample sizes and see if that trend can be observed further. I know that this is not always feasible. IMHO statistics are nice and can help to gain insight into various things. However, for small sample sizes, talking about statistical significance is in my opinion always a bit tricky. If I had to present such results, I would rather refer to the folds by which the data differ, rather than talking about statistics. Because statistical significance and relevance are two different measures ;) Best, Cedric On Saturday, 21. August 2010 15:58:50 Chloe wrote: Hi Cedric, Thanks a lot for your help, after calculating U value using the formula from wikipedia I also found that the W given by R was in fact the U value that I could directly compared to table of critical value. Your advice were really good and useful. I would also be careful with the conclusions of the test due to the limitations you suggested! Have a nice day, Chloé Hi Chloe, first of all, I want to note, that you should be careful using the WMW-test. Even though it is often reported to be some sort of a swiss-army-knife for comparing two distributions, recent research on this test has revelaed that it is crucial what hypotheses you consider. Also the assumptions imposed to the test are critical. For the assumptions, the test basically is a test on identical distributions. For your sample sizes, this is in my opinion quite problematic, as you can not really know what the population distributions look like. Furthermore, the test has shown to be quite strongly influenced by differing variances in the two groups. All this is more or less valid for not necessarily small sample sizes, therefore I am not sure how much it might affect your results. Therefore, caution should be adressed to the interpretation of the results. On Friday, 20. August 2010 19:41:55 Chloe wrote: Dear all, I want to compare the efficiency of 2 methods in extracting proteins from algal samples. I collected 6 independant algal samples and I extracted 3 by the method 1 and 3 others by the method 2. So I have 2 groups of 3 samples, that are not paired. I would like to know if the results obtained by these 2 methods are significantly different, I hope method 2 to be more efficient than method 1. As I have few data I went for the Mann-whitney test: method1=c(35,40,56) method2=c(90,110,115) wilcox.test(method1,method2,paired=FALSE,alternative=less) Wilcoxon rank sum test data: method1 and method2 W = 0, p-value = 0.05 alternative hypothesis: true location shift is less than 0 As I have a small number of samples, I would prefer to compare the U value of the Mann-Whitney test to critical value for table rather than to rely on the p-value. Is W value correspond to U value ? From the help I understand that W=U+m*(m+1)/2, is this true ? In the case it is, my U values would be U=W-6=-6!! I thought that a U value could not be neagtive. Im a little bit puzzled on this one... I would agree with you. I can't really help you with this one right now, but doing the calculation of U manually is not really hard for your problem. All the values from method 2 are higher than the ones from method 1. So the ranking would be: method1 : 1,2,3 method2: 4,5,6 = W(rank sum)_m,n = 1 + 2 + 3 = 6 If I use the definition of U from http://de.wikipedia.org/wiki/Mann-Whitney-U- Test I would calculate U = 0 , which goes with your formula: U = W - 6 = 6 - 6 = 0, what makes sense because the values of X are never greater than the ones of Y. (s. link: the formula for U with the two summations ) Thinking of that, the usage of W in R might simply be misleading and it could indeed represent U. I would be happy to have any information about how to obtain the U value from the Mann-Withney test (wilcox.test()) in order to be able to compare it with table of critical U value commonly found. Thanks a lot for your time and help Have a nice day,
Re: [R] U value from wilcox.test
In addition to Cedric's comments, these are large sample procedures. Your sample sizes are two small. I don't think any procedures using normal approximations are inappropriate for your case. I would suggest making a reasonable distribution on the populations to avoid asymptotic results. -- View this message in context: http://r.789695.n4.nabble.com/U-value-from-wilcox-test-tp2332811p2529823.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] U value from wilcox.test
Hi Cedric, Thanks a lot for your help, after calculating U value using the formula from wikipedia I also found that the W given by R was in fact the U value that I could directly compared to table of critical value. Your advice were really good and useful. I would also be careful with the conclusions of the test due to the limitations you suggested! Have a nice day, Chloé Hi Chloe, first of all, I want to note, that you should be careful using the WMW-test. Even though it is often reported to be some sort of a swiss-army-knife for comparing two distributions, recent research on this test has revelaed that it is crucial what hypotheses you consider. Also the assumptions imposed to the test are critical. For the assumptions, the test basically is a test on identical distributions. For your sample sizes, this is in my opinion quite problematic, as you can not really know what the population distributions look like. Furthermore, the test has shown to be quite strongly influenced by differing variances in the two groups. All this is more or less valid for not necessarily small sample sizes, therefore I am not sure how much it might affect your results. Therefore, caution should be adressed to the interpretation of the results. On Friday, 20. August 2010 19:41:55 Chloe wrote: Dear all, I want to compare the efficiency of 2 methods in extracting proteins from algal samples. I collected 6 independant algal samples and I extracted 3 by the method 1 and 3 others by the method 2. So I have 2 groups of 3 samples, that are not paired. I would like to know if the results obtained by these 2 methods are significantly different, I hope method 2 to be more efficient than method 1. As I have few data I went for the Mann-whitney test: method1=c(35,40,56) method2=c(90,110,115) wilcox.test(method1,method2,paired=FALSE,alternative=less) Wilcoxon rank sum test data: method1 and method2 W = 0, p-value = 0.05 alternative hypothesis: true location shift is less than 0 As I have a small number of samples, I would prefer to compare the U value of the Mann-Whitney test to critical value for table rather than to rely on the p-value. Is W value correspond to U value ? From the help I understand that W=U+m*(m+1)/2, is this true ? In the case it is, my U values would be U=W-6=-6!! I thought that a U value could not be neagtive. Im a little bit puzzled on this one... I would agree with you. I can't really help you with this one right now, but doing the calculation of U manually is not really hard for your problem. All the values from method 2 are higher than the ones from method 1. So the ranking would be: method1 : 1,2,3 method2: 4,5,6 = W(rank sum)_m,n = 1 + 2 + 3 = 6 If I use the definition of U from http://de.wikipedia.org/wiki/Mann-Whitney-U- Test I would calculate U = 0 , which goes with your formula: U = W - 6 = 6 - 6 = 0, what makes sense because the values of X are never greater than the ones of Y. (s. link: the formula for U with the two summations ) Thinking of that, the usage of W in R might simply be misleading and it could indeed represent U. I would be happy to have any information about how to obtain the U value from the Mann-Withney test (wilcox.test()) in order to be able to compare it with table of critical U value commonly found. Thanks a lot for your time and help Have a nice day, Chloé For your sample sizes you can nicely use the critical value tables that can be found easily on the net. I hope I could help with your problem, if not, please feel free to ask further. Best, Cedric __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ View message @ http://r.789695.n4.nabble.com/U-value-from-wilcox-test-tp2332811p2332857.html To unsubscribe from U value from wilcox.test, click http://r.789695.n4.nabble.com/template/NodeServlet.jtp?tpl=unsubscribe_by_codenode=2332811code=Y2hsb2UuYm9ubmluZWF1QHVkZy5lZHV8MjMzMjgxMXwxNTg0NzMxMjA2 -- View this message in context: http://r.789695.n4.nabble.com/U-value-from-wilcox-test-tp2332811p2333515.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] U value from wilcox.test
Glad that I could help :) Another thing that came to my mind ist that when you simply look at the values of the different groups, they differ quite strongly in my opinion. They are between two and three times higher in the second group than the ones from the first group. Therefore it would be a good idea to increase your sample sizes and see if that trend can be observed further. I know that this is not always feasible. IMHO statistics are nice and can help to gain insight into various things. However, for small sample sizes, talking about statistical significance is in my opinion always a bit tricky. If I had to present such results, I would rather refer to the folds by which the data differ, rather than talking about statistics. Because statistical significance and relevance are two different measures ;) Best, Cedric On Saturday, 21. August 2010 15:58:50 Chloe wrote: Hi Cedric, Thanks a lot for your help, after calculating U value using the formula from wikipedia I also found that the W given by R was in fact the U value that I could directly compared to table of critical value. Your advice were really good and useful. I would also be careful with the conclusions of the test due to the limitations you suggested! Have a nice day, Chloé Hi Chloe, first of all, I want to note, that you should be careful using the WMW-test. Even though it is often reported to be some sort of a swiss-army-knife for comparing two distributions, recent research on this test has revelaed that it is crucial what hypotheses you consider. Also the assumptions imposed to the test are critical. For the assumptions, the test basically is a test on identical distributions. For your sample sizes, this is in my opinion quite problematic, as you can not really know what the population distributions look like. Furthermore, the test has shown to be quite strongly influenced by differing variances in the two groups. All this is more or less valid for not necessarily small sample sizes, therefore I am not sure how much it might affect your results. Therefore, caution should be adressed to the interpretation of the results. On Friday, 20. August 2010 19:41:55 Chloe wrote: Dear all, I want to compare the efficiency of 2 methods in extracting proteins from algal samples. I collected 6 independant algal samples and I extracted 3 by the method 1 and 3 others by the method 2. So I have 2 groups of 3 samples, that are not paired. I would like to know if the results obtained by these 2 methods are significantly different, I hope method 2 to be more efficient than method 1. As I have few data I went for the Mann-whitney test: method1=c(35,40,56) method2=c(90,110,115) wilcox.test(method1,method2,paired=FALSE,alternative=less) Wilcoxon rank sum test data: method1 and method2 W = 0, p-value = 0.05 alternative hypothesis: true location shift is less than 0 As I have a small number of samples, I would prefer to compare the U value of the Mann-Whitney test to critical value for table rather than to rely on the p-value. Is W value correspond to U value ? From the help I understand that W=U+m*(m+1)/2, is this true ? In the case it is, my U values would be U=W-6=-6!! I thought that a U value could not be neagtive. Im a little bit puzzled on this one... I would agree with you. I can't really help you with this one right now, but doing the calculation of U manually is not really hard for your problem. All the values from method 2 are higher than the ones from method 1. So the ranking would be: method1 : 1,2,3 method2: 4,5,6 = W(rank sum)_m,n = 1 + 2 + 3 = 6 If I use the definition of U from http://de.wikipedia.org/wiki/Mann-Whitney-U- Test I would calculate U = 0 , which goes with your formula: U = W - 6 = 6 - 6 = 0, what makes sense because the values of X are never greater than the ones of Y. (s. link: the formula for U with the two summations ) Thinking of that, the usage of W in R might simply be misleading and it could indeed represent U. I would be happy to have any information about how to obtain the U value from the Mann-Withney test (wilcox.test()) in order to be able to compare it with table of critical U value commonly found. Thanks a lot for your time and help Have a nice day, Chloé For your sample sizes you can nicely use the critical value tables that can be found easily on the net. I hope I could help with your problem, if not, please feel free to ask further. Best, Cedric __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] U value from wilcox.test
Dear all, I want to compare the efficiency of 2 methods in extracting proteins from algal samples. I collected 6 independant algal samples and I extracted 3 by the method 1 and 3 others by the method 2. So I have 2 groups of 3 samples, that are not paired. I would like to know if the results obtained by these 2 methods are significantly different, I hope method 2 to be more efficient than method 1. As I have few data I went for the Mann-whitney test: method1=c(35,40,56) method2=c(90,110,115) wilcox.test(method1,method2,paired=FALSE,alternative=less) Wilcoxon rank sum test data: method1 and method2 W = 0, p-value = 0.05 alternative hypothesis: true location shift is less than 0 As I have a small number of samples, I would prefer to compare the U value of the Mann-Whitney test to critical value for table rather than to rely on the p-value. Is W value correspond to U value ? From the help I understand that W=U+m*(m+1)/2, is this true ? In the case it is, my U values would be U=W-6=-6!! I thought that a U value could not be neagtive. I would be happy to have any information about how to obtain the U value from the Mann-Withney test (wilcox.test()) in order to be able to compare it with table of critical U value commonly found. Thanks a lot for your time and help Have a nice day, Chloé -- View this message in context: http://r.789695.n4.nabble.com/U-value-from-wilcox-test-tp2332811p2332811.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] U value from wilcox.test
Hi Chloe, first of all, I want to note, that you should be careful using the WMW-test. Even though it is often reported to be some sort of a swiss-army-knife for comparing two distributions, recent research on this test has revelaed that it is crucial what hypotheses you consider. Also the assumptions imposed to the test are critical. For the assumptions, the test basically is a test on identical distributions. For your sample sizes, this is in my opinion quite problematic, as you can not really know what the population distributions look like. Furthermore, the test has shown to be quite strongly influenced by differing variances in the two groups. All this is more or less valid for not necessarily small sample sizes, therefore I am not sure how much it might affect your results. Therefore, caution should be adressed to the interpretation of the results. On Friday, 20. August 2010 19:41:55 Chloe wrote: Dear all, I want to compare the efficiency of 2 methods in extracting proteins from algal samples. I collected 6 independant algal samples and I extracted 3 by the method 1 and 3 others by the method 2. So I have 2 groups of 3 samples, that are not paired. I would like to know if the results obtained by these 2 methods are significantly different, I hope method 2 to be more efficient than method 1. As I have few data I went for the Mann-whitney test: method1=c(35,40,56) method2=c(90,110,115) wilcox.test(method1,method2,paired=FALSE,alternative=less) Wilcoxon rank sum test data: method1 and method2 W = 0, p-value = 0.05 alternative hypothesis: true location shift is less than 0 As I have a small number of samples, I would prefer to compare the U value of the Mann-Whitney test to critical value for table rather than to rely on the p-value. Is W value correspond to U value ? From the help I understand that W=U+m*(m+1)/2, is this true ? In the case it is, my U values would be U=W-6=-6!! I thought that a U value could not be neagtive. Im a little bit puzzled on this one... I would agree with you. I can't really help you with this one right now, but doing the calculation of U manually is not really hard for your problem. All the values from method 2 are higher than the ones from method 1. So the ranking would be: method1 : 1,2,3 method2: 4,5,6 = W(rank sum)_m,n = 1 + 2 + 3 = 6 If I use the definition of U from http://de.wikipedia.org/wiki/Mann-Whitney-U- Test I would calculate U = 0 , which goes with your formula: U = W - 6 = 6 - 6 = 0, what makes sense because the values of X are never greater than the ones of Y. (s. link: the formula for U with the two summations ) Thinking of that, the usage of W in R might simply be misleading and it could indeed represent U. I would be happy to have any information about how to obtain the U value from the Mann-Withney test (wilcox.test()) in order to be able to compare it with table of critical U value commonly found. Thanks a lot for your time and help Have a nice day, Chloé For your sample sizes you can nicely use the critical value tables that can be found easily on the net. I hope I could help with your problem, if not, please feel free to ask further. Best, Cedric __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] U value from wilcox.test
Issues like that in this thread can often be resolved by reading the help page for the relevant function. From: ?wilcox.test Note The literature is not unanimous about the definitions of the Wilcoxon rank sum and Mann-Whitney tests. The two most common definitions correspond to the sum of the ranks of the first sample with the minimum value subtracted or not: R subtracts and S-PLUS does not, giving a value which is larger by m(m+1)/2 for a first sample of size m. (It seems Wilcoxon's original paper used the unadjusted sum of the ranks but subsequent tables subtracted the minimum.) R's value can also be computed as the number of all pairs (x[i], y[j]) for which y[j] is not greater than x[i], the most common definition of the Mann-Whitney test. HTH, Chuck On Fri, 20 Aug 2010, Cedric Laczny wrote: Hi Chloe, first of all, I want to note, that you should be careful using the WMW-test. Even though it is often reported to be some sort of a swiss-army-knife for comparing two distributions, recent research on this test has revelaed that it is crucial what hypotheses you consider. Also the assumptions imposed to the test are critical. For the assumptions, the test basically is a test on identical distributions. For your sample sizes, this is in my opinion quite problematic, as you can not really know what the population distributions look like. Furthermore, the test has shown to be quite strongly influenced by differing variances in the two groups. All this is more or less valid for not necessarily small sample sizes, therefore I am not sure how much it might affect your results. Therefore, caution should be adressed to the interpretation of the results. On Friday, 20. August 2010 19:41:55 Chloe wrote: Dear all, I want to compare the efficiency of 2 methods in extracting proteins from algal samples. I collected 6 independant algal samples and I extracted 3 by the method 1 and 3 others by the method 2. So I have 2 groups of 3 samples, that are not paired. I would like to know if the results obtained by these 2 methods are significantly different, I hope method 2 to be more efficient than method 1. As I have few data I went for the Mann-whitney test: method1=c(35,40,56) method2=c(90,110,115) wilcox.test(method1,method2,paired=FALSE,alternative=less) Wilcoxon rank sum test data: method1 and method2 W = 0, p-value = 0.05 alternative hypothesis: true location shift is less than 0 As I have a small number of samples, I would prefer to compare the U value of the Mann-Whitney test to critical value for table rather than to rely on the p-value. Is W value correspond to U value ? From the help I understand that W=U+m*(m+1)/2, is this true ? In the case it is, my U values would be U=W-6=-6!! I thought that a U value could not be neagtive. Im a little bit puzzled on this one... I would agree with you. I can't really help you with this one right now, but doing the calculation of U manually is not really hard for your problem. All the values from method 2 are higher than the ones from method 1. So the ranking would be: method1 : 1,2,3 method2: 4,5,6 = W(rank sum)_m,n = 1 + 2 + 3 = 6 If I use the definition of U from http://de.wikipedia.org/wiki/Mann-Whitney-U- Test I would calculate U = 0 , which goes with your formula: U = W - 6 = 6 - 6 = 0, what makes sense because the values of X are never greater than the ones of Y. (s. link: the formula for U with the two summations ) Thinking of that, the usage of W in R might simply be misleading and it could indeed represent U. I would be happy to have any information about how to obtain the U value from the Mann-Withney test (wilcox.test()) in order to be able to compare it with table of critical U value commonly found. Thanks a lot for your time and help Have a nice day, Chlo?? For your sample sizes you can nicely use the critical value tables that can be found easily on the net. I hope I could help with your problem, if not, please feel free to ask further. Best, Cedric __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Charles C. Berry(858) 534-2098 Dept of Family/Preventive Medicine E mailto:cbe...@tajo.ucsd.edu UC San Diego http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
