High-dimensional multi-study multi-modality covariate-augmented generalized factor model

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Latent factor models that integrate data from multiple sources/studies or modalities have garnered considerable attention across various disciplines. However, existing methods predominantly focus either on multi-study integration or multi-modality integration, rendering them insufficient for analyzing the diverse modalities measured across multiple studies. To address this limitation and cater to practical needs, we introduce a high-dimensional generalized factor model that seamlessly integrates multi-modality data from multiple studies, while also accommodating additional covariates.

Check out our Biometric paper and Package Website for a more complete description of the methods and analyses.

For more details, see:

Installation

“MMGFM” depends on the ‘Rcpp’ and ‘RcppArmadillo’ package, which requires appropriate setup of computer. For the users that have set up system properly for compiling C++ files, the following installation command will work.

```{Rmd} ## Method 1: if (!require(“remotes”, quietly = TRUE)) install.packages(“remotes”) remotes::install_github(“feiyoung/MMGFM”)

Method 2: install from CRAN

install.packages(“MMGFM”) ```

Usage

For usage examples and guided walkthroughs, check the vignettes directory of the repo.

Simulated codes

For the codes in simulation study, check the simu_code directory of the repo.

News

MMGFM version 1.1 released! (2024-09-17)