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Creating a Pipeline

Add your analysis pipeline steps

add_subgroups()
Add sub groups to the multiverse pipeline
add_filters()
Add filtering/exclusion criteria to a multiverse pipeline
add_variables()
Add a set of variable alternatives to a multiverse pipeline
add_model()
Add a model and formula to a multiverse pipeline
add_model_descriptives()
Add arbitrary summary statistics to a multiverse pipeline
add_preprocess()
Add arbitrary preprocessing code to a multiverse analysis pipeline
add_postprocess()
Add arbitrary postprocessing code to a multiverse pipeline
add_parameter_keys()
Add parameter keys names for later use in summarizing model effects
expand_decisions()
Expand a set of multiverse decisions into all possible combinations

View, Check, and Test

View metadata, check the code, and test the pipeline

visualize_pipeline()
Visualize an analysis pipeline workflow
detect_multiverse_n()
Detect total number of analysis pipelines
detect_n_subgroups()
Detect total number of subgroups in your pipelines
detect_n_filters()
Detect total number of filtering expressions your pipelines
detect_n_variables()
Detect total number of variable sets in your pipelines
detect_n_models()
Detect total number of models in your pipelines
summarize_filter_ns()
Summarize samples sizes for each unique filtering expression
show_code() show_code_subgroups() show_code_filters() show_code_preprocess() show_code_model() show_code_postprocess()
Show multiverse data code pipelines

Run your Pipeline

Execute the whole pipeline and all alternatives

analyze_grid()
Perform all analyses over a complete decision grid
analyze_grid_parallel()
Analyze a complete decision grid in parallel

Unpack Results

Unpack your results for viewing, plotting, and understanding

unpack_specs()
Unpack the decision grid of specifications for your modeling pipeline
unpack_results() unpack_model_parameters() unpack_model_performance() unpack_model_warnings() unpack_model_messages() unpack_postprocess()
Unpack a component of your analyzed grid
condense() organize()
Summarize multiverse parameters
compose_view()
Compose a single analysis-ready data frame from a results grid.

Assess Decision Sensitivity/Robustness

Evaluate the robustness of a model output over the whole decision space, by decision alternatives, or assess the impact of making specific decisions.

assess_robustness()
Assess the robustness of multiverse analysis results
assess_decisions()
Decompose decision variance using Sobol sensitivity indices and variance dispersal

Build a report

Given a set of anlzyed results, incrementally build a polished report

configure_labels()
Configure human-readable labels for pipeline decisions
show_labels()
Inspect or scaffold pipeline labels
add_section()
Add a content section to a report
show_section_content()
Inspect one section's content and code
view_real_size()
Preview a figure at its true output size
preview_section()
Preview a report section's composed layout
initialize_doc()
Begin assembling a report document
layout_section()
Record a section's layout for assembly
generate_docs()
Render an assembled document

Data

coffee_quality
Professional coffee quality ratings

Superseded

Functions that have been replaced by new approaches that are better. These functions still work and will stick around for awhile.

create_blueprint_graph() superseded
Create a Analysis Pipeline diagram

Deprecated

Functions that are no longer supported and will be removed in a future version.