Before testing a specific region using a generalized score type test, this function does the preliminary data management, such as fitting the model under the null hypothesis.

1 |

`Y` |
The outcome variable, an n*1 matrix where n is the total number of observations |

`time` |
An n*2 matrix describing how the observations are measured. The first column is the subject id. The second column is the measured exam (1,2,3,etc.). |

`X` |
An n*p covariates matrix where p is the total number of covariates. |

`corstr` |
The working correlation as specified in 'geeglm'. The following are permitted: "independence", "exchangeable", "ar1". |

It returns a list used for function GA.test().

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
library(LGEWIS)
# Load data example
# Y: outcomes, n by 1 matrix where n is the total number of observations
# X: covariates, n by p matrix
# time: describe longitudinal structure, n by 2 matrix
# G: genotype matrix, m by q matrix where m is the total number of subjects
data(LGEWIS.example)
Y<-LGEWIS.example$Y;time<-LGEWIS.example$time;X<-LGEWIS.example$X;G<-LGEWIS.example$G
# Preliminary data management
result.prelim<-GA.prelim(Y,time,X=X)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.