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The second Section briefly reviews ordinal logistic [ 8] and multinomial logistic [ 9] models and their model assumptions, and also discusses model coefficient estimation methods for both models and the statistical test for checking the ordinal logistic assumption.
The above grid Newton method is used for both ordinal and multinomial logistic model coefficient estimations.
Interpretation of the model coefficients was based on effect estimation rather than hypothesis testing [ 41].
The determination of the model coefficients is based on the estimation of the correlation matrix R ij.
Maximum likelihood estimation yields estimates for the model coefficients (the β's) and exponentiation of the log-odds function then yields the estimates of the individual probabilities.
For the second set of models, the GEEs approach was used for the parameter coefficients estimation and complexities of the design (stratification and clustering) were incorporated via appropriate variance estimation approaches.
The basic test of any model estimation is examination of the sign of model coefficients.
Post hoc tests to compare model coefficients between cohorts were carried out using the Stata suest (seemingly unrelated estimation) command.
Attenuation of model coefficients.
The results show that the theoretical predictions agree fairly well with the experimental results using a combination of Knudsen diffusion and viscous flow models for membrane coefficient estimation.
