Interpreting multinomial logistic results

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SUMMARY

The discussion focuses on interpreting results from a multinomial logistic regression applied to Likert scale survey data assessing teaching assistants (TAs). Key variables include TA training status, international status, and an interaction term between training and international status. The odds ratios reported are 2.8 for trained TAs, 6.9 for international TAs, and 0.5 for the interaction term. The interpretation of the interaction term indicates that the combined effect of being both trained and international results in a lower likelihood of being in the reference group compared to the individual effects of training or international status alone.

PREREQUISITES
  • Understanding of multinomial logistic regression
  • Familiarity with Likert scale data analysis
  • Knowledge of odds ratios and their interpretation
  • Experience with interaction terms in regression models
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  • Research how to interpret interaction terms in multinomial logistic regression
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  • Explore statistical software options for running multinomial logistic regression, such as R or Python's statsmodels
  • Investigate best practices for survey design and analysis of Likert scale data
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Statisticians, data analysts, researchers in social sciences, and anyone involved in interpreting survey data using multinomial logistic regression.

SantyClause
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I ran a multinomial logistic regression on some likart data (1-5 survey response questions). For some background, the survey was sent to undergraduate students to rate their TA on various attributes.

Three of the variables are whether the TA was trained, whether the TA is international, AND an interaction term trained*international. For a particular comparison, I have odds ratio point estimates of 2.8, 6.9, and .5 respectively. I'm fairly certain the 2.8 indicates that being trained means you are 2.8 times more likely to not be in the reference group. Likewise, 6.9 times more likely to not be in the reference group if international. But how do I interpret the last coefficient?
 
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I'm sorry you are not generating any responses at the moment. Is there any additional information you can share with us? Any new findings?
 
What is the dependent variable?
 

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