aSPUw {aSPU} | R Documentation |
It gives the p-values of the SPUw tests and aSPUw test based on the permutations of the residuals or simulations from the null distripution.
aSPUw( Y, X, cov = NULL, resample = c("perm", "boot", "sim"), model = c("gaussian", "binomial"), pow = c(1:8, Inf), n.perm = 1000 )
Y |
Response or phenotype data. It can be a disease indicator; =0 for controls, =1 for cases. Or it can be a quantitative trait. A vector with length n (number of observations). |
X |
Genotype or other data; each row for a subject, and each column for an SNP (or a predictor). The value of each SNP is the # of the copies for an allele. A matrix with dimension n by k (n : number of observation, k : number of SNPs (or predictors) ). |
cov |
Covariates. A matrix with dimension n by p (n :number of observation, p : number of covariates). |
resample |
Use "perm" for residual permutations, "sim" for simulations from the null distribution, and "boot" for parametric bootstrap. |
model |
Use "gaussian" for a quantitative trait, and use "binomial" for a binary trait. |
pow |
power used in SPU test. A vector of the powers. |
n.perm |
number of permutations or bootstraps. |
A list object, Ts : Test Statistics for the SPUw and aSPUw test. pvs : p-values for the SPUw and aSPUw test.
Il-Youp Kwak, Junghi Kim and Wei Pan
Junghi Kim, Jeffrey R Wozniak, Bryon A Mueller, Xiaotong Shen and Wei Pan (2014) Comparison of statistical tests for group differences in brain functional networks, Neuroimage, 1;101:681-694
data(exdat) out <- aSPUw(exdat$Y, exdat$X, pow = c(1:8, Inf), n.perm = 1000) out$Ts # This is a vector of Test Statistics for SPU and aSPU tests. # SPU1 to SPUInf corresponds with the option pow=c(1:8, Inf) # They are SPU test statistics. # The last element aSPU is minimum of them, aSPU statistic. out$pvs # This is a vector of p-values for SPU and aSPU tests. # SPU1 to SPUInf corresponds with the option pow=c(1:8, Inf) # They are p-values for corresponding SPU tests. # The last element is p-value of aSPU test.