For round 1 of stepwise selection modeling, iterate linear regression models, add a new covariate each iteration, and decide whether or not to retain it. In this video, PROC GLM is used and covariates are added in the same order as they were presented in the descriptive table in the previous video.
- [Instructor] All right, now it's time … to start building our model. … You'll see I opened Exercise File … 510_ Stepwise Selection … Linear-Round 1. … The reason it's called this … is because this is indeed round one. … Remember, in round one, it's kind of like a game. … You add an independent variable to your model, run it, … and then look at the P values on the slopes. … You pick out the variables … that are not statistically significant … and decide not to include them in the next model, … then you run the next model, … then you add another covariant and look at the P values … and decide whether or not to keep it. … It's sort of tedious actually. … But in the end, you basically try all your variables once … and either keep them or discard them. … So that's conceptually the first round … of stepwise selection, … but literally, what model do you start with? … I decided to start with this model here. … It's got DIABFLAG in it. … Why? … Because that's the rule. … Since DIABFLAG is our hypothesis, …
Author
Released
4/2/2019- Preparing for linear regression
- Creating plots for testing assumptions
- Linear regression modeling
- Interpreting the linear regression model
- Logistic regression modeling
- Presenting linear and logistic regression models
- Issues in regression
Skill Level Intermediate
Duration
Views
Related Courses
-
Python: Data Analysis
with Michele Vallisneri2h 16m Intermediate -
Analyzing Big Data with Hive
with Ben Sullins1h 53m Intermediate -
Descriptive Healthcare Analytics in R
with Monika Wahi4h 15m Advanced
-
Introduction
-
Introduction to the course1m 52s
-
What you should know3m 2s
-
-
1. Preparing for Linear Regression
-
Basic PROC GLM code3m 7s
-
Reading PROC GLM output5m 56s
-
2. Linear Regression Modeling
-
Linear regression: Round 16m 32s
-
3. Preparing for Logistic Regression
-
Outcome distribution2m 29s
-
Basic PROC LOGISTIC code3m 39s
-
4. Logistic Regression Modeling
-
Logistic regression: Round 15m 52s
-
5. Model Presentation
-
6. Issues in Regression
-
Interaction review6m 56s
-
7. Regression Tips
-
Choosing reference groups5m 10s
-
Conclusion
-
Review of the process2m 50s
-
Next steps5m 40s
-
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.
CancelTake notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.
Share this video
Embed this video
Video: Linear regression: Round 1