Description Usage Arguments Details Value Author(s) References See Also Examples

Fit logistic regression via GEE to test association between a dichotomous phenotype
and one genotyped SNP in a genotype file with user specified genetic model. Each family is treated as
a cluster, with independence working correlation matrix used in the robust variance estimator. The trait-SNP association
test is carried out by the `geese`

function from package `geepack`

.
This function is called in `geepack.lgst.batch`

function to apply association test to all SNPs in the
genotype data.

1 | ```
geepack.lgst(snp, phen, test.dat, covar = NULL, model = "a")
``` |

`snp` |
genotype data of a SNP |

`phen` |
a character string for a phenotype name in |

`test.dat` |
the product of merging phenotype, genotype and pedigree data, should be ordered by "famid" |

`covar` |
a character vector for covariates in |

`model` |
a single character of 'a','d','g', or 'r', with 'a'=additive, 'd'=dominant, 'g'=general and 'r'=recessive models |

The `geepack.lgst`

function tests association between a dichtomous trait and a SNP from a dataset that contains phenotype, genotype and
pedigree data (test.dat), where the dataset needs to be ordered by famid.

Please see output in `geepack.lgst.batch`

.

Qiong Yang <qyang@bu.edu> and Ming-Huei Chen <mhchen@bu.edu>

Liang, K.Y. and Zeger, S.L. (1986)
Longitudinal data analysis using generalized linear models.
*Biometrika*, **73** 13–22.

Zeger, S.L. and Liang, K.Y. (1986)
Longitudinal data analysis for discrete and continuous outcomes.
*Biometrics*, **42** 121–130.

Yan, J and Fine, J. (2004) Estimating equations for association structures. *Stat Med*, **23** 859–874.

`geese`

function from package `geepack`

1 2 3 4 | ```
## Not run:
geepack.lgst(snp=data[,"rs123"],phen="CVD",test.dat=data,model="a",covar=c("age","sex"))
## End(Not run)
``` |

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