1) Fit AFT model including all covariates based on the Lognormal, log-logsitic, Weibull and Generalized Gamma models for Y (totally 3 models) Use LR tests/AIC to determine your initial model

2) Do backward model selection to identify your final model

3) Conduct residual analysis

4) If it fits, write the fitted final model and interpret the model/describe the effects of covariates.

2) Do backward model selection to identify your final model

3) Conduct residual analysis

4) If it fits, write the fitted final model and interpret the model/describe the effects of covariates.

I fitted four models without any interaction term. The LRT and AIC results indicated that Log-Normal model is the best model (Exponential and Weibull reject in LRT), with log-likelihood very close from generalized gamma.

When I should eliminate a variable from the model?

What type of residuals I should check?