Specialist research service · CFA & CB-SEM
Start with measurement: do the indicators support the proposed factors? When the measurement specification is defensible, SEM examines the hypothesized structural relationships within the model.
For research evaluating factor and covariance models, with outputs that help explain the methods and limitations in a thesis, dissertation or paper.
CFA assesses measurement. SEM adds structural relationships specified from theory.
Review convergence, variances, factor correlations and sampling design before interpreting coefficients or fit.
Document the estimator, missing-data treatment, specification changes and how standard errors, p-values and intervals were obtained.
Define the task
The work can proceed in stages. Measurement scales, sampling design and the clarity of the proposed model inform the scope.
Three support options
Start with a CFA review if needed, then agree any structural analysis. Extensions depend on theory, data and suitable estimation methods.
Before finalizing the model
Review the factor specification, questionnaire and available data or results to identify what needs attention.
For researchers doing their own analysis or reviewing a design before further data collection.
Study-specific results
Conduct CFA and any agreed structural analysis, with an explanation of the evidence and its limits.
For researchers with data who need an organized analysis for academic reporting or discussion.
At agreed research milestones
Work through measurement reasoning, model assessment and methodological feedback across agreed review rounds.
For dissertations or papers requiring a clear account of analytical choices and responses to reviewers.
Deliverables, fees and timing are agreed after reviewing the model, sampling design and data. No promise is made that every fit criterion will be met or that hypotheses will be statistically significant.
Deliverables
Confirm the list for your scope. The main report focuses on necessary conclusions; full tables and working files are supplied separately as agreed.
Document the diagram, variable roles, estimator, missing-data treatment and CFA/SEM scope before interpretation.
Report χ², df, CFI, TLI, RMSEA with its interval and SRMR where available, distinguishing conventional and appropriate robust measures.
Standardized loadings, residual variances, CR, AVE and discriminant-validity assessment when applicable. No single statistic establishes validity.
For SEM: B, β, SE, p-values, confidence intervals and R², with the standardization and inference method identified.
Indirect effects, moderation and simple slopes are included only when the theory, design and estimator support them.
Review convergence, improper solutions and negative variances. If bootstrapping is used, report requested, valid and failed draws and the implications for inference.
Organized evidence, diagrams and notes for reporting the findings and limitations, including unfavorable results.
Agreed syntax or model files, settings, software versions and relevant seeds. Data and proprietary software files are covered by the agreed handover.
Working process
Use the contact channel to describe the goal, diagram, measures and data status. Identifiable respondent data are not needed for the initial discussion.
Confirm CFA or SEM, extensions, estimator, deliverables, fees and milestones before sharing the necessary data.
Check the data, identification, convergence and solution; record decisions. Investigate problems before proceeding to inference.
Discuss the main evidence, inspect detailed tables and clarify limitations and remaining research questions.
Data and research responsibility
This page provides service information and contact links; it does not automatically upload survey files. The file-sharing channel, required data and retention arrangements are discussed separately.
Frequently asked questions
CFA assesses factors and their measurement indicators. SEM adds hypothesized relationships between variables or factors. CFA review or analysis can be commissioned separately; proceeding to SEM is not assumed.
The response categories, distribution, missingness and measurement specification matter. Treating items as continuous with ML/MLR needs justification; WLSMV is an option for items declared ordinal. There is no universal default for every survey.
No. Consider the parameter count, measurement quality, distribution, missingness and sampling design. A single row-count threshold does not ensure identification, convergence or adequate power.
The target effect and estimator determine whether bootstrap inference is suitable. Report valid and failed draws. Frequent improper solutions require investigation before relying on intervals; more draws alone do not resolve the cause.
No. Modification indices and residuals support diagnosis. Changes need substantive justification, a record and a distinction from the original hypotheses. Sometimes the appropriate finding is that the measurement or model needs further work.
Comparison requires the same data, specification and estimation settings. AMOS and lavaan differences may reflect settings; CB-SEM and PLS-SEM can also differ in their measurement and estimation approach. Identical coefficients are not promised merely because the same file is used.
A short research goal, diagram, measures, expected or available sample and required outputs. Agree the scope before arranging file transfer, and omit unnecessary respondent identifiers.
They are confirmed after reviewing the model, data condition, extensions and necessary discussion rounds. This page does not assign one fixed fee or delivery time to every study.
Start with your model
Send a short description and your current diagram. We can clarify the CFA/CB-SEM scope and necessary inputs before preparing a quote.
Discuss CFA/CB-SEM