AssotesteR (version 0.1-10)

SCORE: SCORE: Score Test (from Logistic Regression)

Description

The Score test is one of the statistical tests used for logistic regression models, which is one of the standard approaches used in genetic association studies. Under the null hypothesis that there is no associated variants within the examined region, the test statistic has an asymptotic chi-square distribution. In addition, a permutation procedure can be applied to assess the significance of the test.

Usage

SCORE(y, X, perm = 100)

Arguments

y

numeric vector with phenotype status: 0=controls, 1=cases. No missing data allowed

X

numeric matrix or data frame with genotype data coded as 0, 1, 2. Missing data is allowed

perm

positive integer indicating the number of permutations (100 by default)

Value

"assoctest", basically a list with the following elements:

score.stat

score statistic

asym.pval

asymptotic p-value

perm.pval

permuted p-value

args

descriptive information with number of controls, cases, variants, and permutations

name

name of the statistic

Details

There is no imputation for the missing data. Missing values are simply ignored in the computations.

References

Clayton D, Chapman J, Cooper J (2004) Use of unphased multilocus genotype data in indirect association studies. Genetic Epidemiology, 27: 415-428

Chapman J, Whittaker J (2008) Analysis of Multiple SNPs in a Candidate Gene or Region. Genetic Epidemioloy, 32: 560-566

See Also

SSU, SSUW, SUM

Examples

  ## Not run: 
#   
#   # number of cases
#   cases = 500
# 
#   # number of controls
#   controls = 500
# 
#   # total (cases + controls)
#   total = cases + controls
# 
#   # phenotype (first column of genodata)
#   phenotype = c(rep(1, cases), rep(0, controls))
# 
#   # genotype matrix with 10 variants (random data)
#   set.seed(123)
#   genotype = matrix(rbinom(total*10, 2, 0.05), nrow=total, ncol=10)
# 
#   # apply SCORE with 500 permutations
#   myscore = SCORE(phenotype, genotype, perm=500)
#   myscore
#   ## End(Not run)