MS.test {asbio} | R Documentation |
Runs a Mack-Skillings test for situations applicable to rank-based permutation procedures with blocking and more than one replicate for treatments in a block.
MS.test(Y, X, reps)
Y |
A matrix of response data. The |
X |
A vector of treatments. The length of the vector should be equal to the number of rows in the response matrix. |
reps |
The number of replicates in each treatment (unbalanced designs cannot be analyzed). |
When we have more than one replication within a block, and the number of replications is equal for all treatments, we can use the Mack-Skillings test (Mack and Skillings 1980) as a rank based permutation procedure to test for main effect differences. If ties occur the value of the significance level is only approximate. Hollander and Wolfe (1996) provide a method for finding exact P-values by deriving a test statistic distribution allowing ties.
Returns a dataframe summarizing the degrees of freedom, test statistic and p-value.
Ken Aho
Campbell, J. A., and O. Pelletier (1962) Determination of niacin (niacinamide) in cereal products. J. Assoc. Offic. Anal. Chem. 45: 449-453.
Hollander, M., and D. A. Wolfe (1999) Nonparametric Statistical Methods. New York: John Wiley & Sons.
Mack, G. A., and J. H. Skillings (1980) A Friedman-type rank test for main effects in a two-factor ANOVA. Journal of the American Statistical Association. 75: 947-951.
#data from Campbell and Pelletier (1962) Niacin0<-c(7.58,7.87,7.71,8.00,8.27,8,7.6,7.3,7.82,8.03,7.35,7.66) Niacin4<-c(11.63,11.87,11.40,12.20,11.70,11.80,11.04,11.50,11.49,11.50,10.10,11.70) Niacin8<-c(15.00,15.92,15.58,16.60,16.40,15.90,15.87,15.91,16.28,15.10,14.80,15.70) Niacin<-cbind(Niacin0,Niacin4,Niacin8) lab<-c(rep(1,3),rep(2,3),rep(3,3),rep(4,3)) MS.test(Niacin, lab, reps=3)