Package index • VaSSTra

Complete workflow

Run the whole variables-to-trajectories analysis in one call.

vasstra(): Run the Complete VaSSTra Workflow

Explicit steps

The four steps vasstra() runs, for full control over each stage.

step1_states(): Step 1: Turn Variables into States
step2_sequences(): Step 2: Turn States into Sequences
step3_trajectories(): Step 3: Turn Sequences into Trajectories
step4_describe(): Step 4: Describe the Trajectories

Choosing and evaluating a model

Compare cluster counts and methods, and read fit statistics.

evaluate(): Evaluate a Fitted Clustering
fit_indices(): Tidy Fit Indices for a Fitted Clustering
state_choices(): Compare Choices for the Number and Method of States
trajectory_choices(): Compare Choices for the Number and Method of Trajectories
fit_state_choice(): Fit One State Choice
fit_trajectory_choice(): Fit One Trajectory Choice

Plots

Sequence, trajectory, state, and evaluation views, plus transition networks and state-flow diagrams.

plot(<vasstra>): Plot a Complete VaSSTra Analysis
plot(<vasstra_states>): Plot Estimated VaSSTra States
plot(<vasstra_sequences>): Plot VaSSTra State Sequences with Nestimate
plot(<vasstra_trajectories>): Plot VaSSTra Trajectories with Nestimate
plot(<vasstra_evaluation>): Plot a Clustering Evaluation
plot(<vasstra_evaluations>): Plot the Evaluations of a Complete Fit
plot(<vasstra_state_choices>): Plot State-Clustering Choices
plot(<vasstra_trajectory_choices>): Plot Trajectory-Clustering Choices
transition_plot(): Plot the State Transition Network
transition_centrality(): State Transition Network Centralities
flow_plot(): Plot State Flows Between Consecutive Time Points

Labels and tidy output

Rename groups after inspection and extract tidy tables.

set_labels(): Relabel Fitted States or Trajectories
as.data.frame(<vasstra>): Convert a VaSSTra Analysis to a Tidy Table

Interactive app

launch_app(): Launch the Interactive VaSSTra App

Data

engagement: Longitudinal Student Engagement