I will advanced glm, mixed effects, regression analysis in r

For your your need please contact for a custom offer.

I cover a comprehensive range of advanced statistical frameworks, including-

Mixed-Effects Models: Linear & Generalized Linear Mixed Models (LMM/GLMM) with random intercepts and slopes.

Generalized Linear Models (GLM): Logistic (Binomial), Poisson, Negative Binomial, and Gamma Regression.

Categorical & Count Data: Log-linear analysis, contingency tables, and rate modeling.

Advanced Regression: Polynomial, Ridge/Lasso, and Multinomial Logistic Regression.

Key services I offer,

Pre-Analysis & Data Hygiene

• Outlier detection and treatment
• Data transformation (Log, Square Root, Box-Cox) to meet model assumptions.

Rigorous Assumption Testing

• Normality : Shapiro-Wilk, Kolmogorov-Smirnov tests, and Q-Q plots.
• Homoscedasticity: Breusch-Pagan and White tests.
• Independence: Durbin-Watson test for autocorrelation.
• Multicollinearity: Variance Inflation Factor (VIF) and Tolerance metrics.

Residual Diagnostics & Model Validation

• Visual and statistical validation of error terms.
• Diagnostic plots (Residuals vs. Fitted, Scale-Location, Residuals vs. Leverage).
• Model comparison using AIC, BIC, and Log-Likelihood ratio tests.