Bass-Ackwards Hierarchical Structural Analysis

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Documentation for package ‘ackwards’ version 0.1.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

ackwards	Bass-ackwards hierarchical structural analysis
augment.ackwards	Augment data with factor scores from an ackwards object
autoplot	autoplot generic
autoplot.ackwards	Plot a bass-ackwards diagram or per-level fit index chart
autoplot.comparability	Plot a comparability diagnostic
autoplot.suggest_k	Plot a suggest_k diagnostic
ba_layout	Compute a layered layout for a bass-ackwards diagram
bfi25	Big Five Inventory - 25-item IPIP example dataset
boot_edges	Bootstrap confidence intervals for between-level edges
boot_edges.ackwards	Bootstrap confidence intervals for between-level edges
check_items	Screen items for problems before factor analysis
comparability	Split-half factor comparability
factorability	Screen a dataset for factorability and sampling adequacy
factor_labels	Read the factor labels stored on an ackwards object
forbes2023	Assessing Mental Health symptom correlation matrix (Forbes 2023 applied example)
glance.ackwards	Glance at an ackwards object
label_template	Generate a node-label scaffold for autoplot
plot.ackwards	Plot a bass-ackwards diagram or per-level fit index chart
predict.ackwards	Score new observations with a fitted ackwards model
print.ackwards	Print an ackwards object
print.ackwards_labels	Generate a node-label scaffold for autoplot
print.check_items	Print an item quality check
print.comparability	Print a comparability object
print.factorability	Print a factorability screen
print.suggest_k	Print a suggest_k object
print.summary_ackwards	Print a summary_ackwards object
print.top_items	Print a top_items object
prune	Flag redundant or artifactual factors (Forbes 2023 extension)
prune.ackwards	Flag redundant or artifactual factors (Forbes 2023 extension)
set_factor_labels	Attach persistent factor labels to an ackwards object
sim16	Simulated continuous bass-ackwards teaching example (16 items, known hierarchy)
suggest_k	Suggest a maximum number of factors for bass-ackwards analysis
summary.ackwards	Summarise an ackwards object
tidy.ackwards	Tidy an ackwards object into a long data frame
top_items	Display the salient items for each factor