Description: Resolves complex metagenomic mixtures by analysing
deep sequencing data, using a mixture model based approach.

Author: Isabelle Weir [aut, cre], Lu Tian [aut], Ludovic Trinquart [aut]
Description: R implementation of a multivariate meta-analysis of randomized controlled trials (RCT) with the difference in restricted mean survival times (RMSTD). Use this package with individual patient level data from an RCT for a time-to-event outcome to determine combined effect estimates according to 4 methods: 1)  a univariate meta-analysis using observed treatment effects, 2) a univariate meta-analysis using effects predicted by fitted Royston-Parmar flexible parametric models, 3) multivariate meta-analysis with analytically derived covariance, 4) multivariate meta-analysis with bootstrap derived covariance. This package computes all combined effects and provides an RMSTD curve with combined effect estimates and their confidence intervals.
Imports: mvmeta, meta, survival, survRM2, graphics

Author: Guillemette Marot, Florence Jaffrezic, Andrea Rau
Description: This package implements two p-value combination techniques (inverse normal and Fisher methods). It also provides a vignette explaining how to combine data from multiple RNA-seq experiments.

Description: Implementation of two p-value combination techniques (inverse normal and Fisher methods). A vignette is provided to explain how to perform a meta-analysis from two independent RNA-seq experiments.

Author: Guillemette Marot  [aut, cre], Andrea Rau  [aut, cre], Florence Jaffrezic [aut], Samuel Blanck [ctb]
Suggests: DESeq2 (>= 1.0.17), VennDiagram (>= 1.6.20)

Title: Regression Models for Meta Signal Detection Theory
email = "simonbk@ph.au.dk", role = c("aut", "cre"))
Description: Regression methods for the meta-SDT model. The package implements methods for cognitive experiments of meta cognition as described in Kristensen, S. B., Sandberg, K., & Bibby, B. M. (2020). Regression methods for metacognitive sensitivity. Journal of Mathematical Psychology, 94. <doi:10.1016/j.jmp.2019.102297>.
Author: Simon Bang Kristensen [aut, cre]
Maintainer: Simon Bang Kristensen <simonbk@ph.au.dk>