Package index • ackwards

Fit the model

The main modelling function, a Forbes-style pruning verb, and pre-analysis helpers for screening items, choosing k, and gating hierarchy depth on replicability.

ackwards(): Bass-ackwards hierarchical structural analysis
prune(): Flag redundant or artifactual factors (Forbes 2023 extension)
boot_edges(): Bootstrap confidence intervals for between-level edges
check_items(): Screen items for problems before factor analysis
print(<check_items>): Print an item quality check
factorability(): Screen a dataset for factorability and sampling adequacy
print(<factorability>): Print a factorability screen
suggest_k(): Suggest a maximum number of factors for bass-ackwards analysis
print(<suggest_k>): Print a suggest_k object
autoplot(<suggest_k>): Plot a suggest_k diagnostic
comparability(): Split-half factor comparability
print(<comparability>): Print a comparability object
autoplot(<comparability>): Plot a comparability diagnostic

Interpret factors

Helpers for understanding what each factor means and labelling it.

top_items(): Display the salient items for each factor
print(<top_items>): Print a top_items object
label_template() print(<ackwards_labels>): Generate a node-label scaffold for autoplot
set_factor_labels(): Attach persistent factor labels to an ackwards object
factor_labels(): Read the factor labels stored on an ackwards object

Extract results

Tidy, glance, augment, predict, summary, and print methods for ackwards objects.

tidy(<ackwards>): Tidy an ackwards object into a long data frame
glance(<ackwards>): Glance at an ackwards object
augment(<ackwards>): Augment data with factor scores from an ackwards object
predict(<ackwards>): Score new observations with a fitted ackwards model
summary(<ackwards>): Summarise an ackwards object
print(<ackwards>): Print an ackwards object
print(<summary_ackwards>): Print a summary_ackwards object

Low-level utilities

Functions for advanced use or building on top of ackwards results.

compute_edges(): Compute between-level factor-score correlations

Visualize

Diagram and layout helpers for the bass-ackwards hierarchy.

autoplot(): autoplot generic
autoplot(<ackwards>) plot(<ackwards>): Plot a bass-ackwards diagram or per-level fit index chart
ba_layout(): Compute a layered layout for a bass-ackwards diagram

Data

Example datasets bundled with the package.

bfi25: Big Five Inventory – 25-item IPIP example dataset
sim16: Simulated continuous bass-ackwards teaching example (16 items, known hierarchy)
forbes2023: Assessing Mental Health symptom correlation matrix (Forbes 2023 applied example)

Re-exported generics

Generics re-exported from the generics package so they work after library(ackwards) without also loading broom.

reexports augment tidy glance: Objects exported from other packages