Full SEM Testing — Initial Structural Model

Table of Contents

• Scope Boundary
• Workflow
• Decision Tree
• Required Inputs
• Code Structure
• Reporting Standards
• Method Status
• Minimal Smoke Test
• Failure Modes

Open-source skill.

Scope Boundary

Use this skill when:

• The model includes both a measurement component and structural paths among latent and/or observed variables.
• A first-pass SEM fit is needed before indirect-effect bootstrapping, multigroup comparison, or model revision.

Do not use this skill when:

• The task is CFA-only without structural paths; use vera-data-cfa-reviewing.
• The core question is longitudinal growth / change; use vera-data-growth-reviewing.

Workflow

Read each step file in workflow/ before executing that step.

Step	Responsibility	Executor	Document	Input	Output
Collect	Collect Inputs	Main Agent	workflow/step01-collect-inputs.md	User input	Structured SEM summary
Diagnose	Check Model Setup	Main Agent	workflow/step02-check-model-setup.md	Prior step output	Identification + estimator decision
Test	Run Primary Sem	Main Agent	workflow/step03-run-primary-sem.md	Prior step output	Initial SEM fit + recommendation

Decision Tree

1. CHECK MEASUREMENT COMPONENT
   ├── latent factors specified → SEM path
   └── only observed variables → consider path analysis, but keep SEM framing explicit

2. CHECK STRUCTURAL COMPONENT
   ├── direct paths only → baseline SEM
   ├── mediation present → label indirect paths for later testing
   └── multigroup / longitudinal / nonlinear elements → recommend specialized SEM skills

3. CHECK ESTIMATOR
   ├── continuous indicators → ML / MLR
   └── categorical indicators → WLSMV / DWLS

Required Inputs

Role	What to collect
Latent constructs	Factor names, theoretical meaning, indicators per factor
Structural paths	Which latent/observed variables predict which
Mediators	Any indirect paths (X → M → Y)
Scale type	Continuous, ordinal/Likert, binary indicators
Grouping variable	Optional; for later multi-group comparison
Sample size	Final analytic N and missing-data context

Code Structure

PART 0: Setup & Data Loading
PART 1: Model Setup Checks (identification, estimator)
PART 2: Primary SEM Fit (global fit + structural coefficients)
PART 3: Recommendation Block

Reporting Standards

1. Always report chi-square, df, CFI, TLI, RMSEA, and SRMR
2. Report standardized path coefficients with SE or CI
3. Report R-squared for endogenous latent variables
4. Identification problems must be stated explicitly, never silently patched
5. Mediation paths: label but do not test significance (recommend full analysis)
6. Ends with recommendation block for mediation testing, multi-group analysis, model modification, and indirect effect bootstrapping
7. Fit-index thresholds: CFI / TLI ≥ 0.90 (≥ 0.95 preferred); RMSEA ≤ 0.08 (≤ 0.06 preferred); SRMR ≤ 0.08. For ordinal/categorical indicators with DWLS/WLSMV, report robust variants.

Method Status

Status	Methods
Implemented in this skill	Structural-model setup checks, initial SEM fit, global fit reporting, key path reporting, mediation-path labeling
Implemented downstream in vera-data-path-generating	Indirect-effect bootstrapping, multigroup SEM, alternative-path comparison, residual review, manuscript assembly
Out of scope in this open-source baseline	Longitudinal growth SEM and latent-model families not explicitly named above

Minimal Smoke Test

• Smoke-test prompt: "Run vera-data-path-reviewing on a small mediation-style SEM with two latent factors and one structural path chain. Produce the standard baseline artifacts and recommendation block."

Next step: Invoke vera-data-path-generating from this skillset to run the full pipeline (indirect-effect bootstrap CIs, multi-group SEM, alternative-path comparison, manuscript generation). See ../../CROSS-SKILL-INTERFACE.md for the shared handoff contract.

Failure Modes

• If model does not converge: report non-convergence, suggest simplifying structure
• If outcome type is CFA-only (no structural paths): redirect to vera-data-cfa-reviewing
• If longitudinal growth structure detected: redirect to vera-data-growth-reviewing