summary.snpLong {SimHap} | R Documentation |
Summary method for objects of class snpLong
## S3 method for class 'snpLong': summary(object, ...) ## S3 method for class 'summary.snpLong': print(x, digits = max(3, getOption("digits") - 3), signif.stars = getOption("show.signif.stars"), ...)
object |
an object of class snpLong , a result of a call to snp.long . |
x |
an object of class summary.snpLong , the result of a call to summary.snpLong. |
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.snpLong
returns an object of class summary.snpLong
. Some components taken from summary.lme. A list with components
call |
the formula call. |
terms |
terms attribute of the formula called in snp.long . |
fixDF |
as per lmeObject . A list with components X and terms specifying the denominator degrees of freedom for, respectively, t-tests for the individual fixed effects and F-tests for the fixed-effects terms in the models. |
sigma |
as per lmeObject . The estimated within-group error standard deviation. |
groups |
as per lmeObject . A data frame with the grouping factors as columns. The grouping level increases from left to right. |
dims |
as per lmeObject . A list with basic dimensions used in the lme fit, including the components N - the number of observations in the data, Q - the number of grouping levels, qvec - the number of random effects at each level from innermost to outermost (last two values are equal to zero and correspond to the fixed effects and the response), ngrps - the number of groups at each level from innermost to outermost (last two values are one and correspond to the fixed effects and the response), and ncol - the number of columns in the model matrix for each level of grouping from innermost to outermost (last two values are equal to the number of fixed effects and one). |
method |
as per lmeObject . The estimation method: either ``ML" for maximum likelihood, or ``REML" for restricted maximum likelihood. |
coefficients |
summarized results from fitted model, including coefficients, standard errors and p-values. |
formula |
fixed effects formula used in snp.long . |
residuals |
as per lmeObject . If more than five observations are used in the lme fit, a vector with the minimum, first quartile, median, third quartile, and maximum of the innermost grouping level residuals distribution; else the innermost grouping level residuals. |
AIC |
Akaike Information Criterion for the model fitted in snp.long . |
corStruct |
the correlation structure specified in snp.long . |
modelStruct |
as per lmeObject . An object inheriting from class lmeStruct , representing a list of mixed-effects model components, such as reStruct , corStruct , and varFunc objects. |
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(SNPlong.dat) # transforms SNPlong.dat to an object containing 3 columns # per SNP - additive, dominant and recessive, where genotypes # defined in 'baseline' serve as the baseline genotypes longGeno.dat <- SNP2Geno(SNPlong.dat, baseline=c("AA", "GG", "V2V2")) data(longPheno.dat) mymodel <- snp.long(fixed=fev1f~SNP_1_add, random=~1|id, geno=longGeno.dat, pheno=longPheno.dat, form=~year|id) summary(mymodel)