| summary.snpBin {SimHap} | R Documentation |
Summary method for objects of class snpBin
## S3 method for class 'snpBin':
summary(object, ...)
## S3 method for class 'summary.snpBin':
print(x, digits = max(3, getOption("digits") - 3),
signif.stars = getOption("show.signif.stars"), ...)
object |
object of class snpBin, the result of a call to snp.bin. |
x |
an object of class summary.snpBin, the result of a call to summary.snpBin. |
digits |
the number of significant digits to use when printing. |
signif.stars |
logical. If TRUE, ``significance stars" are printed for each coefficient. |
... |
further arguments passed to or from other methods. |
summary.snpBin returns an object of class summary.snpBin, a list
with components
call |
the formula call. |
terms |
terms attribute of the formula called in snp.bin. |
df.residual |
the residual degrees of freedom. |
df |
degrees of freedom parameter used in printing the model summary. |
residuals |
as per glm. The working residuals, that is the residuals in the final iteration of the IWLS fit. Since cases with zero weights are omitted, their working residuals are NA. |
coefficients |
summarized results from fitted model, including odds ratios, confidence intervals and p-values. |
formula |
formula1 used in snp.bin. |
LRT |
a likelihood ratio test, testing for significant improvement of the model when SNP parameters are included. |
weights |
as per glm. The working weights, that is the weights in the final iteration of the IWLS fit. |
AIC |
Akaike Information Criterion for the generalized linear model fit including SNPs. |
Pamela A. McCaskie
McCaskie, P.A., Carter, K.W. Hazelton, M., Palmer, L.J. (2007) SimHap: A comprehensive modeling framework for epidemiological outcomes and a multiple-imputation approach to haplotypic analysis of population-based data, [online] www.genepi.org.au/simhap.
data(SNP.dat)
# convert SNP.dat to format required by snp.bin
geno.dat <- SNP2Geno(SNP.dat, baseline=c("MM", "11", "GG", "CC"))
data(pheno.dat)
mymodel <- snp.bin(formula1=PLAQUE~AGE+SEX+SNP_1_add,
formula2=PLAQUE~AGE+SEX, geno=geno.dat, pheno=pheno.dat)
summary(mymodel)