bama - High Dimensional Bayesian Mediation Analysis
Perform mediation analysis in the presence of high-dimensional mediators based on the potential outcome framework. Bayesian Mediation Analysis (BAMA), developed by Song et al (2019) <doi:10.1111/biom.13189> and Song et al (2020) <arXiv:2009.11409>, relies on two Bayesian sparse linear mixed models to simultaneously analyze a relatively large number of mediators for a continuous exposure and outcome assuming a small number of mediators are truly active. This sparsity assumption also allows the extension of univariate mediator analysis by casting the identification of active mediators as a variable selection problem and applying Bayesian methods with continuous shrinkage priors on the effects.
Last updated 2 years ago
openblascpp
4.80 score 1 dependents 42 scripts 393 downloadsSynDI - Synthetic Data Integration
Regression inference for multiple populations by integrating summary-level data using stacked imputations. Gu, T., Taylor, J.M.G. and Mukherjee, B. (2021) A synthetic data integration framework to leverage external summary-level information from heterogeneous populations <arXiv:2106.06835>.
Last updated 3 years ago
4.30 score 2 stars 7 scripts 198 downloadssnSMART - Small N Sequential Multiple Assignment Randomized Trial Methods
Consolidated data simulation, sample size calculation and analysis functions for several snSMART (small sample sequential, multiple assignment, randomized trial) designs under one library. See Wei, B., Braun, T.M., Tamura, R.N. and Kidwell, K.M. "A Bayesian analysis of small n sequential multiple assignment randomized trials (snSMARTs)." (2018) Statistics in medicine, 37(26), pp.3723-3732 <doi:10.1002/sim.7900>.
Last updated 5 months ago
bayesian-analysisclinical-trialsrare-diseasesmall-samplejagscpp
3.90 score 1 stars 3 scripts 282 downloadsAEenrich - Adverse Event Enrichment Tests
We extend existing gene enrichment tests to perform adverse event enrichment analysis. Unlike the continuous gene expression data, adverse event data are counts. Therefore, adverse event data has many zeros and ties. We propose two enrichment tests. One is a modified Fisher's exact test based on pre-selected significant adverse events, while the other is based on a modified Kolmogorov-Smirnov statistic. We add Covariate adjustment to improve the analysis."Adverse event enrichment tests using VAERS" Shuoran Li, Lili Zhao (2020) <arXiv:2007.02266>.
Last updated 2 years ago
3.48 score 3 stars 1 scripts 296 downloadsPPMR - Probabilistic Two Sample Mendelian Randomization
Efficient statistical inference of two-sample MR (Mendelian Randomization) analysis. It can account for the correlated instruments and the horizontal pleiotropy, and can provide the accurate estimates of both causal effect and horizontal pleiotropy effect as well as the two corresponding p-values. There are two main functions in the 'PPMR' package. One is PMR_individual() for individual level data, the other is PMR_summary() for summary data.
Last updated 6 years ago
openblascppopenmp
3.28 score 2 stars 19 scripts 140 downloadsmessi - Mediation with External Summary Statistic Information
Fits the MESSI, hard constraint, and unconstrained models in Boss et al. (2023) <doi:10.48550/arXiv.2306.17347> for mediation analyses with external summary-level information on the total effect.
Last updated 2 months ago
3.18 score 3 scripts 261 downloadsStackImpute - Tools for Analysis of Stacked Multiple Imputations
Provides methods for inference using stacked multiple imputations augmented with weights. The vignette provides example R code for implementation in general multiple imputation settings. For additional details about the estimation algorithm, we refer the reader to Beesley, Lauren J and Taylor, Jeremy M G (2020) “A stacked approach for chained equations multiple imputation incorporating the substantive model” <doi:10.1111/biom.13372>, and Beesley, Lauren J and Taylor, Jeremy M G (2021) “Accounting for not-at-random missingness through imputation stacking” <arXiv:2101.07954>.
Last updated 3 years ago
3.18 score 1 dependents 7 scripts 199 downloadsqif - Quadratic Inference Function
Developed to perform the estimation and inference for regression coefficient parameters in longitudinal marginal models using the method of quadratic inference functions. Like generalized estimating equations, this method is also a quasi-likelihood inference method. It has been showed that the method gives consistent estimators of the regression coefficients even if the correlation structure is misspecified, and it is more efficient than GEE when the correlation structure is misspecified. Based on Qu, A., Lindsay, B.G. and Li, B. (2000) <doi:10.1093/biomet/87.4.823>.
Last updated 6 years ago
fortranopenblas
3.18 score 1 dependents 2 scripts 179 downloadsmedScan - Large Scale Single Mediator Hypothesis Testing
A collection of methods for large scale single mediator hypothesis testing. The six included methods for testing the mediation effect are Sobel's test, Max P test, joint significance test under the composite null hypothesis, high dimensional mediation testing, divide-aggregate composite null test, and Sobel's test under the composite null hypothesis. Du et al (2023) <doi:10.1002/gepi.22510>.
Last updated 12 months ago
3.00 score 5 scripts 213 downloadsgigg - Group Inverse-Gamma Gamma Shrinkage for Sparse Regression with Grouping Structure
A Gibbs sampler corresponding to a Group Inverse-Gamma Gamma (GIGG) regression model with adjustment covariates. Hyperparameters in the GIGG prior specification can either be fixed by the user or can be estimated via Marginal Maximum Likelihood Estimation. Jonathan Boss, Jyotishka Datta, Xin Wang, Sung Kyun Park, Jian Kang, Bhramar Mukherjee (2021) <arXiv:2102.10670>.
Last updated 3 years ago
openblascpp
2.70 score 1 scripts 187 downloadsFEprovideR - Fixed Effects Logistic Model with High-Dimensional Parameters
A structured profile likelihood algorithm for the logistic fixed effects model and an approximate expectation maximization (EM) algorithm for the logistic mixed effects model. Based on He, K., Kalbfleisch, J.D., Li, Y. and Li, Y. (2013) <doi:10.1007/s10985-013-9264-6>.
Last updated 6 years ago
2.70 score 1 stars 1 scripts 119 downloadsINTRIGUE - Quantify and Control Reproducibility in High-Throughput Experiments
Estimate the proportions of the null and the reproducibility and non-reproducibility of the signal group for the input data set. The Bayes factor calculation and EM (Expectation Maximization) algorithm procedures are also included.
Last updated 4 years ago
2.48 score 2 scripts 116 downloads
hlt - Higher-Order Item Response Theory
Higher-order latent trait theory (item response theory). We implement the generalized partial credit model with a second-order latent trait structure. Latent regression can be done on the second-order latent trait. For a pre-print of the methods, see, "Latent Regression in Higher-Order Item Response Theory with the R Package hlt" <https://mkleinsa.github.io/doc/hlt_proof_draft_brmic.pdf>.
Last updated 3 years ago
cpp
1.70 score 6 scripts 353 downloads