R for Logistic Regression: Livestream Recording
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This livestream event was originally recorded on September 5, 2023.
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Links/Timestamps from Video:
0:51 Why software integration in public health? Why now? And how?
2:15 SAS is great at logistic regression, but here are some pain points R can solve
6:03 Explanation of R GUI vs. RStudio – how they are alike and different
8:03 Typical approach in SAS for logistic regression
8:54 Check out Monika’s LinkedIn Learning courses on study design, and how she applies this approach to both SAS and R: https://buff.ly/3xWjYT7
9:48 What do the slopes mean from the logistic regression equation?
10:57 What’s the difference in approach when moving from SAS to R when doing logistic regression?
12:00 Description of example dataset from BRFSS
12:39 R GUI interface
13:42 How to map R GUI session to a folder with the dataset in it using the menu, and how to import dataset
15:48 Setting up a hypothesis for logistic regression in public health
18:57 Code to express hypothesized equation in R
19:42 Options for model fit statistics in R
20:42 Getting and interpreting the SAS-like output from R
24:18 Turning output into *.csv format and adding an OR and confidence limits on-the-fly!
29:08 Interpreting the same model on the OR scale – public health interpretation!
31:15 What if you have a model with 15 covariates instead of only 3? How do you write about this in the results section?
34:57 Making the coefficient plot with library ARM
40:45 Monika’s “colors in R” blog post: https://buff.ly/3ehoiWo
41:52 Recap of all the steps in the pipeline Monika demonstrated for logistic regression in R
45:00 Monika answers question, “What do you recommend for sample size calculation?”