SmartPLS Structural Model Analysis
Budget: $50 – $150 USD
I have collected 100 complete survey responses and am ready to run a structural equation model in SmartPLS. The model contains 6 latent variables and I have already defined the specific hypotheses that link them. What I now need is a clear, statistically sound SEM analysis and a concise interpretation of the findings.
Here is what I will provide upfront: the cleaned data file (CSV or Excel), a diagram of the proposed paths, the hypothesis list, and the measurement items mapped to each construct. Your task is to load everything into SmartPLS, estimate the structural model, and confirm or reject the hypotheses by reporting path coefficients, t-values, p-values, and R². Please ensure all usual diagnostics—bootstrapping, discriminant validity, reliability, multicollinearity checks—are covered so I can include them in my methodology section.
Deliverables
• The completed SmartPLS project file (.splsm)
• An export of key results
• A brief write-up (1–2 pages) that explains the statistical output in plain language and highlights which hypotheses are supported
If you spot any data issues or feel additional refinements could improve model fit, flag them and propose solutions—I’m open to suggestions as long as we stay within SmartPLS. Turnaround within a few days is ideal so I can move straight to drafting the results chapter.
Here is what I will provide upfront: the cleaned data file (CSV or Excel), a diagram of the proposed paths, the hypothesis list, and the measurement items mapped to each construct. Your task is to load everything into SmartPLS, estimate the structural model, and confirm or reject the hypotheses by reporting path coefficients, t-values, p-values, and R². Please ensure all usual diagnostics—bootstrapping, discriminant validity, reliability, multicollinearity checks—are covered so I can include them in my methodology section.
Deliverables
• The completed SmartPLS project file (.splsm)
• An export of key results
• A brief write-up (1–2 pages) that explains the statistical output in plain language and highlights which hypotheses are supported
If you spot any data issues or feel additional refinements could improve model fit, flag them and propose solutions—I’m open to suggestions as long as we stay within SmartPLS. Turnaround within a few days is ideal so I can move straight to drafting the results chapter.