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Grid ordinal and multinomial logistic models were introduced in detail.
We used multinomial logistic models to investigate the relationship between MD and Sorlie Perou subtypes.
Before we introduce our method we first introduce both ordinal and multinomial logistic models in a few more detail.
Second, we ran multinomial logistic models with the three partner types as outcomes and to directly compare odds ratios across destinations.
Both results of the binary logistic regression and multinomial logistic models were presented as odds ratio with their corresponding 95% confidence intervals (CI).
The multinomial logistic models estimate separate relative risk ratios for having each of one or two ears affected (rather than none).
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The multinomial logistic model will then lead to a response behavior, which is apparently unrealistic.
Multilevel multinomial logistic modeling was used to analyze the risk factors and changes of undermet needs over time.
To identify the variables independently associated with asymptomatic malaria, we performed a multinomial logistic model with adjustment for the all variables studied.
The multinomial logistic model was used to fit the dataset.
The above grid Newton method is used for both ordinal and multinomial logistic model coefficient estimations.
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