lmPBJ.RdThis function computes a statistical map and residuals which are the objects necessary to perform the parametric bootstrap joint (PBJ) inference procedure.
lmPBJ(images, form, formred, mask, data = NULL, W = NULL,
Winv = NULL, template = NULL, formImages = NULL, robust = TRUE,
sqrtSigma = TRUE, transform = TRUE, outdir = NULL,
mc.cores = getOption("mc.cores", 2L))| images | Character vector of subject images to be modeled as an outcome variable OR 4d array of imaging data OR 4d nifti object. |
|---|---|
| form | formula or character that can be coerced to a formula or a design matrix for the full model. |
| formred | formula or character that can be coerced to a formula or a design matrix for reduced model. If robust=TRUE then this must have one less column than X. |
| mask | File name for a binary mask file or niftiImage object. |
| data | R data frame containing variables in form. If form and formred are matrices then this can be NULL. |
| W | Weights for regression model. Can be used to deweight noisy observations. Same as what should be passed to lm. |
| Winv | Inverse weights for regression model. Inverse of W. Required when passing variance images as the inverse weights. |
| template | Template image used for visualization. |
| formImages | n X p matrix of images where n is the number of subjects and each column corresponds to an imaging covariate. Currently, not supported. |
| robust | Logical, compute robust standard error estimates? Defaults to TRUE. Uses HC3 SE estimates from Long and Ervin 2000. |
| sqrtSigma | Logical: return V X n matrix sqrtSigma? Defaults to TRUE (described below). Required to use pbj function. |
| transform | Logical: use transformation from equation (5) of Vandekar et al. 2019 (Biometrics)? Defaults to TRUE. (instead of niftiImage objects; defaults to FALSE). |
| outdir | If specified, output is saved as NIfTIs and statMap object is saved as strings. This approach conserves memory, but has longer IO time. Currently, not supported. |
| mc.cores | Argument passed to mclapply for parallel things. |
Returns a list with the following values:
The statistical values where mask!=0. If ncol(X) = ncol(Xred)+1, then this is a Z-statistic map, otherwise it is a chi^2-statistic map.
A 4d niftiImage giving the parameter estimates for covariates only in the full model.
The covariance object. This is a V by n matrix R, such that R %*% t(R) = hatSigma.
The input mask.
The background template used for visualization.
A list containing the full and reduced models.
A logical indicating the input setting.
The numerator degrees of freedom of the test.
The numerator degrees of freedom of the test.
stat=stat, sqrtSigma=res, mask=mask, template=template, formulas=list(form, formred), robust=robust, df=df, rdf=rdf