All packages

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memuse — 4.2-3

Memory Estimation Utilities

MendelianRandomization — 0.10.0

Mendelian Randomization Package

MEPDF — 3.0

Creation of Empirical Density Functions Based on Multivariate Data

Mercator — 1.1.4

Clustering and Visualizing Distance Matrices

merDeriv — 0.2-4

Case-Wise and Cluster-Wise Derivatives for Mixed Effects Models

mergen — 0.2.1

AI-Driven Code Generation, Explanation and Execution for Data Analysis

mergeTrees — 0.1.3

Aggregating Trees

mergingTools — 1.0.1

Tools to Merge Hardware Event Monitors (HEMs) Coming from Separate Subexperiments into One Single Dataframe

merlin — 0.1.0

Mixed Effects Regression for Linear, Non-Linear and User-Defined Models

MERO — 0.1.2

Performing Monte Carlo Expectation Maximization Random Forest Imputation for Biological Data

merror — 3.0

Accuracy and Precision of Measurements

merTools — 0.6.2

Tools for Analyzing Mixed Effect Regression Models

meshed — 0.2.3

Bayesian Regression with Meshed Gaussian Processes

MESS — 0.5.12

Miscellaneous Esoteric Statistical Scripts

messaging — 0.1.0

Conveniently Issue Messages, Warnings, and Errors

messi — 0.1.1

Mediation Analysis with External Summary-Level Information on Total Effect

messy.cats — 1.0

Employs String Distance Tools to Help Clean Categorical Data

messydates — 0.4.1

A Flexible Class for Messy Dates

Mestim — 0.2.1

Computes the Variance-Covariance Matrix of Multidimensional Parameters Using M-Estimation

meta — 7.0-0

General Package for Meta-Analysis

meta.shrinkage — 0.1.4

Meta-Analyses for Simultaneously Estimating Individual Means

meta4diag — 2.1.1

Meta-Analysis for Diagnostic Test Studies

MetaAnalyser — 0.2.1

An Interactive Visualisation of Meta-Analysis as a Physical Weighing Machine

metabias — 0.1.1

Meta-Analysis for Within-Study and/or Across-Study Biases

metaBLUE — 1.0.0

BLUE for Combining Location and Scale Information in a Meta-Analysis

metaBMA — 0.6.9

Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis

metaboData — 0.6.3

Example Metabolomics Data Sets

MetabolAnalyze — 1.3

Probabilistic latent variable models for metabolomic data.

metabolic — 0.1.2

Datasets and Functions for Reproducing Meta-Analyses

MetabolicSurv — 1.1.2

A Biomarker Validation Approach for Classification and Predicting Survival Using Metabolomics Signature

MetabolicSyndrome — 0.1.3

Diagnosis of Metabolic Syndrome

MetabolomicsBasics — 1.4.5

Basic Functions to Investigate Metabolomics Data Matrices

MetaboQC — 1.1

Normalize Metabolomic Data using QC Signal

metabup — 0.1.3

Bayesian Meta-Analysis Using Basic Uncertain Pooling

metacart — 2.0-3

Meta-CART: A Flexible Approach to Identify Moderators in Meta-Analysis

metaCluster — 0.1.1

Metagenomic Clustering

metacoder — 0.3.7

Tools for Parsing, Manipulating, and Graphing Taxonomic Abundance Data

metacom — 1.5.3

Analysis of the 'Elements of Metacommunity Structure'

MetaComp — 1.1.2

EDGE Taxonomy Assignments Visualization

metaconfoundr — 0.1.2

Visualize 'Confounder' Control in Meta-Analyses

metaConvert — 1.0.0

An Automatic Suite for Estimation of Various Effect Size Measures

metacore — 0.1.3

A Centralized Metadata Object Focus on Clinical Trial Data Programming Workflows

MetaculR — 0.4.1

Analyze Metaculus Predictions and Questions

MetaCycle — 1.2.0

Evaluate Periodicity in Large Scale Data

metadat — 1.2-0

Meta-Analysis Datasets

metadeconfoundR — 1.0.2

Covariate-Sensitive Analysis of Cross-Sectional High-Dimensional Data

metaDigitise — 1.0.1

Extract and Summarise Data from Published Figures

metadynminer — 0.1.7

Tools to Read, Analyze and Visualize Metadynamics HILLS Files from 'Plumed'

metadynminer3d — 0.0.2

Tools to Read, Analyze and Visualize Metadynamics 3D HILLS Files from 'Plumed'

metaEnsembleR — 0.1.0

Automated Intuitive Package for Meta-Ensemble Learning

metafolio — 0.1.2

Metapopulation Simulations for Conserving Salmon Through Portfolio Optimization

metafor — 4.6-0

Meta-Analysis Package for R

metaforest — 0.1.4

Exploring Heterogeneity in Meta-Analysis using Random Forests

metafuse — 2.0-1

Fused Lasso Approach in Regression Coefficient Clustering

metagam — 0.4.0

Meta-Analysis of Generalized Additive Models

metaGE — 1.0.3

Meta-Analysis for Detecting Genotype x Environment Associations

metagear — 0.7

Comprehensive Research Synthesis Tools for Systematic Reviews and Meta-Analysis

metaggR — 0.3.0

Calculate the Knowledge-Weighted Estimate

MetaHD — 0.1.1

A Multivariate Meta-Analysis Model for Metabolomics Data

metaheuristicOpt — 2.0.0

Metaheuristic for Optimization

metainc — 0.2-0

Assessment of Inconsistency in Meta-Analysis using Decision Thresholds

MetaIntegration — 0.1.2

Ensemble Meta-Prediction Framework

MetaIntegrator — 2.1.3

Meta-Analysis of Gene Expression Data

MetaLandSim — 2.0.0

Landscape and Range Expansion Simulation

metaLik — 0.43.0

Likelihood Inference in Meta-Analysis and Meta-Regression Models

metalite — 0.1.3

ADaM Metadata Structure

metalite.ae — 0.1.2

Adverse Events Analysis Using 'metalite'

metalite.table1 — 0.4.0

Interactive Table of Descriptive Statistics in HTML

MetaLonDA — 1.1.8

Metagenomics Longitudinal Differential Abundance Method

MetAlyzer — 1.0.0

Read and Analyze 'MetIDQ™' Software Output Files

metaMA — 3.1.3

Meta-Analysis for MicroArrays

metamedian — 1.1.1

Meta-Analysis of Medians

metamer — 0.3.0

Create Data with Identical Statistics

metamicrobiomeR — 1.2

Microbiome Data Analysis & Meta-Analysis with GAMLSS-BEZI & Random Effects

metamisc — 0.4.0

Meta-Analysis of Diagnosis and Prognosis Research Studies

metan — 1.18.0

Multi Environment Trials Analysis

MetaNet — 0.1.2

Network Analysis for Omics Data

metanetwork — 0.7.0

Handling and Representing Trophic Networks in Space and Time

MetaNLP — 0.1.2

Natural Language Processing for Meta Analysis

metansue — 2.5

Meta-Analysis of Studies with Non-Statistically Significant Unreported Effects

metap — 1.10

Meta-Analysis of Significance Values

metapack — 0.3

Bayesian Meta-Analysis and Network Meta-Analysis

metaplot — 0.8.4

Data-Driven Plot Design

metaplus — 1.0-4

Robust Meta-Analysis and Meta-Regression

metapost — 1.0-6

Interface to 'MetaPost'

metapower — 0.2.2

Power Analysis for Meta-Analysis

metapro — 1.5.11

Robust P-Value Combination Methods

metaprotr — 1.2.2

Metaproteomics Post-Processing Analysis

metaRange — 1.1.4

Framework to Build Mechanistic and Metabolic Constrained Species Distribution Models

metarep — 1.2.0

Replicability-Analysis Tools for Meta-Analysis

metaRNASeq — 1.0.7

Meta-Analysis of RNA-Seq Data

metaSDTreg — 0.2.2

Regression Models for Meta Signal Detection Theory

metaSEM — 1.4.0

Meta-Analysis using Structural Equation Modeling

metasens — 1.5-2

Statistical Methods for Sensitivity Analysis in Meta-Analysis

MetaSKAT — 0.82

Meta Analysis for SNP-Set (Sequence) Kernel Association Test

MetaStan — 1.0.0

Bayesian Meta-Analysis via 'Stan'

MetaSubtract — 1.60

Subtracting Summary Statistics of One or more Cohorts from Meta-GWAS Results

metaSurvival — 0.1.0

Meta-Analysis of a Single Survival Curve

metatest — 1.0-5

Fit and Test Metaregression Models

metathis — 1.1.4

HTML Metadata Tags for 'R Markdown' and 'Shiny'

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