fitNullReg {GENESIS} | R Documentation

## 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. This function is deprecated; use `fitNullModel` instead.

### Usage

    fitNullReg(scanData, outcome, covars = NULL, scan.include = NULL,
                family = gaussian, verbose = TRUE)

### Arguments

`scanData` | An object of class `ScanAnnotationDataFrame` from the package `GWASTools`, `AnnotatedDataFrame`, or class `data.frame` containing the outcome and covariate data for the samples to be used for the analysis. `scanData` must have a column `scanID` containing unique IDs for all samples.
`outcome` | A character string specifying the name of the outcome variable in `scanData`.
`covars` | A vector of character strings specifying the names of the fixed effect covariates in `scanData`; an intercept term is automatically included. If NULL (default) the only fixed effect covariate is the intercept term.
`scan.include` | A vector of scanIDs for samples to include in the analysis. If NULL, all samples in `scanData` are included.
`family` | A description of the error distribution to be used in the model. The default "gaussian" fits a linear model; see `family` for further options.
`verbose` | Logical indicator of whether updates from the function should be printed to the console; the default is TRUE.

### Value

An object of class '`GENESIS.nullModel`'. 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 `covars`.
`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 `family` is gaussian, this is just the original outcome vector. When `family` is not gaussian, this is the PQL linearization of the outcome vector. This is used by `assocTestSeq` for genetic association testing.
`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

[Package GENESIS version 2.12.4 Index]