SmartPLS SEM Analysis Services

Our specialized SmartPLS analysis services offer researchers rigorous support for Partial Least Squares Structural Equation Modeling (PLS-SEM). Unlike covariance-based methods, our approach is particularly robust for complex models, non-normal data distributions, and studies with smaller sample sizes. We ensure methodological precision by evaluating both reflective and formative measurement models and conducting advanced mediation and moderation tests to validate your theoretical framework. You will receive a comprehensive, publication-ready interpretation of your findings in MS Word and PDF, guaranteeing your dissertation meets the highest academic standards.

SmartPLS Services

SmartPLS Analysis Pricing and Plans

We offer transparent and competitive pricing for our statistical consulting services using SmartPLS. Whether you are working on a Master’s thesis or a Doctoral dissertation, you can choose a plan that fits your budget and research complexity. Please review the options below to find the best package for your study.

SmartPLS Analysis Service Packages and Pricing

Service Tier Academic Level Hypothesis Scope Revisions Price
Standard Analysis
(Basic Modeling)
Master’s Thesis Up to 5 Hypotheses 2 Rounds $100
Advanced Analysis
(Complex Modeling)
Doctoral Dissertation More than 5 Hypotheses Unlimited (Until Approval) $150

We provide specialized statistical consulting at Wordona for researchers employing Partial Least Squares Structural Equation Modeling (PLS-SEM). We specialize in the application of SmartPLS to conduct rigorous assessments of measurement models and intricate path analyses. We guarantee the precise evaluation of reliability and validity metrics, alongside hypothesis testing, to substantiate complex theoretical frameworks, ensuring results that adhere to the highest academic standards.

Measurement Model Assessment with SmartPLS

Structural modeling requires a rigorous validation of the measurement model before testing relationships. Using SmartPLS, we evaluate the construct validity and reliability of the observed variables to establish strong links between indicators and their latent constructs. We conduct a thorough analysis of Factor Loadings, Internal Consistency (Cronbach’s Alpha and Composite Reliability), Convergent Validity (AVE), and Discriminant Validity (HTMT and Fornell-Larcker criteria) to ensure the scale is psychometrically sound. This preliminary step ensures that the subsequent testing of structural hypotheses rests on valid and robust data structures.

Structural Model Evaluation

After testing the measurement model, we proceed to the Structural Model Evaluation, where the hypothesized causal relationships among latent constructs are tested. To accurately accept or reject research hypotheses, we use SmartPLS to perform the bootstrapping procedure, calculating standardized path coefficients, t-statistics, and p-values. Moreover, we measure the explanatory strength and predictive capability of the model by evaluating the R-square, Effect Size, and Predictive Relevance. This ensures that the suggested theoretical framework is supported by the data and is of sufficient strength to be interpreted academically.

Mediation and Moderation Analysis

We are able to go beyond the direct correlation ability to explore more complicated underlying processes using the Mediation and Modernization analysis. To carefully estimate confidence intervals and determine the significance of indirect effects that answer the question of how and why, we apply the bootstrapping approach-the gold standard of SEM-so, we understand the cause and effect relationships among variables. We also do moderation analysis, typically using Multi-Group Analysis (MGA) when there are categorical moderators or interaction terms with continuous variables to establish the conditions of the relationship which weaker or stronger. This subtle methodology gives you a better understanding of your information, which is needed in a critique-chapter level discussion.

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