Full SEM Testing — Initial Structural Model
Table of Contents
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
- Always report
chi-square, df, CFI, TLI, RMSEA, and SRMR
- Report standardized path coefficients with SE or CI
- Report R-squared for endogenous latent variables
- Identification problems must be stated explicitly, never silently patched
- Mediation paths: label but do not test significance (recommend full analysis)
- Ends with recommendation block for mediation testing,
multi-group analysis, model modification, and indirect effect bootstrapping
- 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
1---2name: vera-data-path-reviewing3description: Structural equation modeling skill. Collects latent constructs and path structure, checks identification and estimator requirements, fits one primary SEM, and reports global fit plus key structural paths with a recommendation block for advanced analyses. Trigger when the user asks for SEM, latent path analysis, full structural equation modeling, path coefficients, structural paths, mediation model, latent variable model, causal SEM, direct and indirect effects, or path diagram. Does not handle CFA-only models (use vera-data-cfa-reviewing) or longitudinal growth models (use vera-data-growth-reviewing).4---56# Full SEM Testing — Initial Structural Model78## Table of Contents910- [Scope Boundary](#scope-boundary)11- [Workflow](#workflow)12- [Decision Tree](#decision-tree)13- [Required Inputs](#required-inputs)14- [Code Structure](#code-structure)15- [Reporting Standards](#reporting-standards)16- [Method Status](#method-status)17- [Minimal Smoke Test](#minimal-smoke-test)18- [Failure Modes](#failure-modes)192021Open-source skill.2223## Scope Boundary2425Use this skill when:26- The model includes both a measurement component and structural paths among latent and/or observed variables.27- A first-pass SEM fit is needed before indirect-effect bootstrapping, multigroup comparison, or model revision.2829Do not use this skill when:30- The task is CFA-only without structural paths; use `vera-data-cfa-reviewing`.31- The core question is longitudinal growth / change; use `vera-data-growth-reviewing`.3233## Workflow3435Read each step file in `workflow/` before executing that step.3637| Step | Responsibility | Executor | Document | Input | Output |38|---|---|---|---|---|---|39| Collect | Collect Inputs | Main Agent | `workflow/step01-collect-inputs.md` | User input | Structured SEM summary |40| Diagnose | Check Model Setup | Main Agent | `workflow/step02-check-model-setup.md` | Prior step output | Identification + estimator decision |41| Test | Run Primary Sem | Main Agent | `workflow/step03-run-primary-sem.md` | Prior step output | Initial SEM fit + recommendation |4243## Decision Tree4445```461. CHECK MEASUREMENT COMPONENT47 ├── latent factors specified → SEM path48 └── only observed variables → consider path analysis, but keep SEM framing explicit49502. CHECK STRUCTURAL COMPONENT51 ├── direct paths only → baseline SEM52 ├── mediation present → label indirect paths for later testing53 └── multigroup / longitudinal / nonlinear elements → recommend specialized SEM skills54553. CHECK ESTIMATOR56 ├── continuous indicators → ML / MLR57 └── categorical indicators → WLSMV / DWLS58```5960## Required Inputs6162| Role | What to collect |63|---|---|64| **Latent constructs** | Factor names, theoretical meaning, indicators per factor |65| **Structural paths** | Which latent/observed variables predict which |66| **Mediators** | Any indirect paths (X → M → Y) |67| **Scale type** | Continuous, ordinal/Likert, binary indicators |68| **Grouping variable** | Optional; for later multi-group comparison |69| **Sample size** | Final analytic N and missing-data context |7071## Code Structure7273```74PART 0: Setup & Data Loading75PART 1: Model Setup Checks (identification, estimator)76PART 2: Primary SEM Fit (global fit + structural coefficients)77PART 3: Recommendation Block78```7980## Reporting Standards81821. Always report `chi-square`, `df`, `CFI`, `TLI`, `RMSEA`, and `SRMR`832. Report standardized path coefficients with SE or CI843. Report R-squared for endogenous latent variables854. Identification problems must be stated explicitly, never silently patched865. Mediation paths: label but do not test significance (recommend full analysis)876. Ends with recommendation block for mediation testing,88 multi-group analysis, model modification, and indirect effect bootstrapping897. **Fit-index thresholds**: CFI / TLI ≥ 0.90 (≥ 0.95 preferred); RMSEA ≤ 0.08 (≤ 0.06 preferred);90 SRMR ≤ 0.08. For ordinal/categorical indicators with DWLS/WLSMV, report robust variants.9192## Method Status9394| Status | Methods |95|---|---|96| Implemented in this skill | Structural-model setup checks, initial SEM fit, global fit reporting, key path reporting, mediation-path labeling |97| Implemented downstream in `vera-data-path-generating` | Indirect-effect bootstrapping, multigroup SEM, alternative-path comparison, residual review, manuscript assembly |98| Out of scope in this open-source baseline | Longitudinal growth SEM and latent-model families not explicitly named above |99100## Minimal Smoke Test101102- 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."103104Next step: Invoke `vera-data-path-generating` from this skillset105to run the full pipeline (indirect-effect bootstrap CIs, multi-group SEM, alternative-path comparison,106manuscript generation). See `../../CROSS-SKILL-INTERFACE.md` for the shared handoff contract.107108## Failure Modes109110- If model does not converge: report non-convergence, suggest simplifying structure111- If outcome type is CFA-only (no structural paths): redirect to `vera-data-cfa-reviewing`112- If longitudinal growth structure detected: redirect to `vera-data-growth-reviewing`
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