Multimodal Mediation Analysis
Pretty Printing
Convert mediation_data to a single data.frame
Bootstrap Distribution for Estimators
Bayesian Regression Model across Responses
Sample from a Bayesian Regression Model
Estimate the Difference between Profiles
Difference between Samples at Contrasting Profiles
A Demo Dataset (Random)
A Demo Dataset (Spline)
Direct Effects from Estimated Model
Access Mediation Model DAG
Graphical Structure for Mediation Objects
Average Effects across j
Estimate a Mediation Model
Accessor for Estimators
Accessor for Model Estimators
Convert a Summarized Experiment to a data.frame
Calibration using Synthetic Nulls
Regularized 'Glmnet' Model across Responses
Sample from a 'Glmnet' Package Model
Overall Indirect Effect
Indirect Effects via Single Mediation Paths
Linear Model across Responses
Sample a Linear Model
Logistic Normal Multinomial Model
Sample from the Logistic Normal Multinomial
mediation_data Constructor
Accessor for Outcome Models
Access to @mediators in Mediation Data
Names of Mediators in a Multimedia Object
Set the Mediators in a Mediation Data Object
Set Mediators
Access Class-Specific Mediators
Representation of an Outcome or Mediation Model
multimedia Constructor
Number of Mediators in a Multimedia Object
Number of Outcomes in a Multimedia Object
How many samples in the mediation dataset?
Compare Effects from Experimental vs. Null Mediation Data
Nullify Active Edges
Access the Outcome Model in a Multimedia Object
Accessor for Outcome Models
Outcomes Data in a Mediation Data Object
Names of Outcomes in a Multimedia Object
Set the Outcomes in a Mediation Data Object
Set Outcomes This is an setter method for outcomes in an S4 object, us...
Access Outcomes
Parallelize Estimation across Responses
Visualize Indirect Effects
Generic Sensitivity Plot
Predict a Subset of Responses
Predictions from a Multimedia Class
Pretreatments in a Mediation Data Object
Set the Pretreatments in a Mediation Data Object
Set Pretreatments This is an setter method for pretreatments in an S4 ...
Access Pretreatments
Variables in a Multimedia Object
Random Forest Model
Sample from a Random Forest Model
Sample New Mediator/Outcome Data
Sensitivity Analysis for Pathwise Indirect Effects
Sensitivity to User-Specified Perturbations
Sensitivity Analysis for Overall Indirect Effect
Define a treatment_profile object
Generate Random Spline
Helper to Modify Formulas
Subset a mediation dataset
Define a Treatment Profile
Treatments in a Mediation Data Object
Names of Treatments in a Multimedia Object
Set the Treatments in a Mediation Data Object
Set Treatments This is an setter method for treatments in an S4 object...
Access Treatments
Multimodal mediation analysis is an emerging problem in microbiome data analysis. Multimedia make advanced mediation analysis techniques easy to use, ensuring that all statistical components are transparent and adaptable to specific problem contexts. The package provides a uniform interface to direct and indirect effect estimation, synthetic null hypothesis testing, bootstrap confidence interval construction, and sensitivity analysis. More details are available in Jiang et al. (2024) "multimedia: Multimodal Mediation Analysis of Microbiome Data" <doi:10.1101/2024.03.27.587024>.
Useful links