Assessing-Model-Goodness-of-Fit-to-the-Data.md

@@ -36,4 +36,8 @@ Information criteria can be used for both nested and non-nested models. Here we
 
 <img src="https://latex.codecogs.com/svg.latex?AIC&space;=&space;-2ln(L(M_1))&plus;2Q&space;\\&space;\\&space;\indent&space;BIC&space;=&space;-2ln(L(M_1))&plus;Qln(N)" title="AIC = -2ln(L(M_1))+2Q \\ \\ \indent BIC = -2ln(L(M_1))+Qln(N)" />
 
-where Q equals the number of parameters in the model and N is the sample size. **Smaller values of AIC and BIC indicate better models.**
\ No newline at end of file
+where Q equals the number of parameters in the model and N is the sample size. **Smaller values of AIC and BIC indicate better models.**
+
+**Important:** When using AIC and BIC to compare models, the same dataset should be used for both models. This becomes relevant when some cases are excluded from a model due to missing values on some of the variables. 
+
+### 4. Local Measures of Fit 
\ No newline at end of file