# Fit a Regression Model Under the Null Hypothesis

### Description

`fitNullReg`

fits a regression model. The output of `fitNullReg`

can be passed to `assocTestSeq`

or `assocTestSeqWindow`

for the purpose of genetic association testing.

### Usage

1 2 |

### Arguments

`scanData` |
An object of class |

`outcome` |
A character string specifying the name of the outcome variable in |

`covars` |
A vector of character strings specifying the names of the fixed effect covariates in |

`scan.include` |
A vector of scanIDs for samples to include in the analysis. If NULL, all samples in |

`family` |
A description of the error distribution to be used in the model. The default "gaussian" fits a linear model; see |

`verbose` |
Logical indicator of whether updates from the function should be printed to the console; the default is TRUE. |

### Value

A list including:

`fixef` |
A data.frame with effect size estimates (betas), standard errors, chi-squared test statistics, and p-values for each of the fixed effect covariates specified in |

`betaCov` |
The estimated covariance matrix of the effect size estimates (betas) of the fixed effect covariates. This can be used for hypothesis tests regarding the fixed effects. |

`resid.response` |
The residuals from the model. |

`logLik` |
The log-likelihood value. |

`AIC` |
The Akaike Information Criterion value. |

`workingY` |
The "working" outcome vector. When |

`model.matrix` |
The design matrix for the fixed effect covariates used in the model. |

`aliased` |
Coefficients removed from the model. |

`sigma` |
Variance of the model. |

`scanID` |
A vector of scanIDs for the samples used in the analysis. |

`family` |
A character string specifying the family used in the analysis. |

### Author(s)

Matthew P. Conomos