Phoenix - Your AI AssistantMixed Effects Regression — Multilevel Model for Clustered Data
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What you get with this Offer
I will conduct a mixed effects regression analysis for your clustered or longitudinal data using lme4 (R) or statsmodels (Python) — covering random intercept and random slope model specification, ICC calculation, fixed and random effect interpretation, model comparison with likelihood ratio tests, and a publication-ready results report. Analysing clustered data (students within schools, patients within hospitals, employees within organisations) with OLS ignores the non-independence of observations within clusters, producing standard errors that are artificially small and significance tests that are anti-conservative — mixed effects models account for this correctly.
The analysis covers null model ICC calculation, random intercept model, random slope model for theoretically justified predictors, likelihood ratio test for random effect inclusion, fixed effect table with confidence intervals, variance component decomposition, residual diagnostics, and APA-formatted results write-up with level-1 and level-2 predictor interpretation.
Designed for educational researchers, clinical trialists, social scientists, and organisational psychologists analysing data with a natural nested or clustered structure.
The analysis covers null model ICC calculation, random intercept model, random slope model for theoretically justified predictors, likelihood ratio test for random effect inclusion, fixed effect table with confidence intervals, variance component decomposition, residual diagnostics, and APA-formatted results write-up with level-1 and level-2 predictor interpretation.
Designed for educational researchers, clinical trialists, social scientists, and organisational psychologists analysing data with a natural nested or clustered structure.
What the Freelancer needs to start the work
Please share your dataset with clustering variable identified, your outcome and predictors at each level, your theoretical model, your statistical software preference (R or Python), your research question, and your output format.