epi.quant {SimHap} | R Documentation |
epi.quant
is used to fit linear regression models to single SNP genotype and phenotype data for a continuous Normal outcome.
epi.quant(formula, pheno, sub = NULL)
formula |
a symbolic description of the full model to be fit. The details of model specification are given below. |
pheno |
a dataframe containing phenotype data. |
sub |
an expression representing a subset of the data on which to perform the models. |
formula
should be in the form of response ~ predictor(s)
. A formula has an implied intercept term. See documentation for formula
function for more details of allowed formulae.
epi.quant
returns an object of class epiQuant
containing the following items
formula |
formula passed to epi.quant. |
results |
a table containing the coefficients, standard errors and p-values of the parameter estimates. |
fit.lm |
a lm object fit using formula. |
ANOD |
analysis of deviance table for the model fit using formula. |
logLik |
the log-likelihood for the linear model fit using formula. |
AIC |
Akaike Information Criterion for the linear model fit using formula. |
Pamela A. McCaskie
Chambers, J.M. (1992) Linear models. Chapter 4 of Statistical Models in S, eds Chambers, J.M., Hastie, T.J., Wadsworth & Brooks/Cole.
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.
Wilkinson, G.N., Rogers, C.E. (1973) Symbolic descriptions of factorial models for analysis of variance. Applied Statistics, 22, 392-9.
snp.quant
, haplo.quant
, epi.bin
data(pheno.dat) mymodel <- epi.quant(formula=LDL~AGE+SBP, pheno=pheno.dat) summary(mymodel) # example with a subsetting variable, looking at males only mymodel <- epi.quant(formula=LDL~AGE+SBP, pheno=pheno.dat, sub=expression(SEX==1))