row.slr.shapiro {HybridMTest} | R Documentation |
For each row of the data matrix Y, use the Shapiro-Wilk test to determine if the residuals of simple linear regression on x are normally distributed.
row.slr.shapiro(Y, x)
Y |
a data matrix with rows for variables and columns for subjects |
x |
a vector with values of the independent variables for regression of each row of Y. |
A data.frame with three columns:
stat |
A vector with the Shapiro-Wilk test statistic for each row of Y |
pval |
A vector with the Shapiro-Wilk p-value for each row of Y |
ebp |
A vector with the estimated empirical Bayes probability of normally distributed residuals for each row of Y |
Stan Pounds <stanley.pounds@stjude.org>; Demba Fofana <demba.fofana@stjude.org>
Patrick Royston (1982) Algorithm AS 181: The W test for Normality. Applied Statistics, 31, 176-180.
####################Correlation Study##################### # load data data(correlation.data) # Read the expression values Y<-exprs(correlation.data) # Read the phenotype x<-pData(correlation.data) x[,1] #Shapiro Test row.slr.shapiro(Y,x[,1])