- [Instructor] This movie continues my explanation…of the rounds in forward stepwise…logistic regression modeling.…This time, we are focused on round three.…Round three is particularly important…because it's where you achieve your final, final model.…You want it to be a robust model.…I'll explain what that means.…You do that by trying to break the working final model,…also called the candidate final model…we talked about in the last movie.…We did this in logistic regression too,…but I wanted to go over it again here…to make sure you understand…exactly what we are trying to achieve.…
So at the start of round three,…you have a candidate final model,…also called a working final model…that came out of round two.…All of the covariates in it should be significant…or close to significant.…You run the show, you make the call.…If you think a covariate is empirically important,…meaning you think it just belongs there, keep it.…This can happen when a covariate is almost significant…like with a P value of 0.08, between 0.05 and 0.10.…
Author
Released
1/19/2017- Dealing with scientific plausibility
- Selecting a hypothesis
- Interpreting diagnostic plots
- Working with indexes and model metadata
- Working with quartiles and ranking
- Making a working model
- Improving model fit
- Performing linear regression modeling
- Performing logistic regression modeling
- Performing forward stepwise regression
- Estimating parameters
- Interpreting an odds ratio
- Adding odds ratios to models
- Comparing nested models
- Presenting and interpreting the final model
Skill Level Advanced
Duration
Views
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Introduction
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Introduction to the course1m 40s
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1. Designing Your Research
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Scientific method review5m 13s
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2. Preparing for Linear Regression
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Indexes7m 20s
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Quartiles3m 41s
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Ranking4m 45s
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Regression review3m 53s
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Preparing to report results2m 39s
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3. Beginning Linear Regression Modeling
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Overview of modeling process4m 58s
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Linear regression output5m 29s
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Models 1 and 23m 21s
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Model metadata4m 20s
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4. Final Linear Regression Modeling
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Beginning Model 35m 7s
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Making a working Model 35m 23s
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Finalizing Model 33m 33s
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Looking at the final model5m 58s
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Fishing and interaction5m 5s
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Defending the final model4m 27s
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Presenting the final model6m 27s
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5. Preparing for Logistic Regression
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Odds ratio interpretation6m 26s
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Basic logistic code3m 53s
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6. Developing the Logistic Regression Model
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Running Model 15m 24s
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Adding odds ratios to models5m 35s
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Model metadata6m 36s
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Forward stepwise: Round 25m 53s
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Models 1 and 2 presentation6m 30s
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Model 3 presentation4m 14s
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Conclusion
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Review of metadata4m 41s
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Review of the process3m 21s
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Next steps2m 19s
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Video: Forward stepwise regression: Round 3