Multinomial Versus Ordinal: Does Model Selection Make a Difference?

Regression modeling, a foundational component of data analysis and machine learning, is one of the most highly sought-after skills by employers seeking new data scientists. While most data science curricula tend to include regression modeling techniques, the conceptual nuances between theoretical and practical applications can be nebulous. In this paper, we use SAS® 9.4 software and the ICPSR 2016 Monitoring Futures Survey to demonstrate the utility and effects of model selection on context. That is, the ability of the model to properly communicate the users intended information. A cross-sectional secondary analysis using Pearson’s Chi-Square test statistic for independence was conducted on the 2016 Monitoring Futures Study data set to determine the association between “behavior risk” (v7335) and each of the three predictor variables, “parental communication” (v7254), “time spent alone after school” (loner) and student letter grades (v7221). Next, two logistic models were computed using these predictors. Statistically significant associations were identified, and adjusted odds ratios were produced using both multinomial and ordinal regression models. Output from both models was evaluated and compared to demonstrate the utility of ordinal modeling (and output) as a “higher-view” and generalizing procedure, whereas multinomial models are more appropriate for a more detailed view of group-level comparisons.

Presenter: Corey Leadbeater, MS, Data Scientist, 8People, Inc.
Session ID: 4853
Topic: Analytics
Industry: Life Sciences
Audience: Other
Skill Level: Intermediate
Sessions to get Excited About Contest Entry – https://www.youtube.com/watch?v=J4hN7Bx_DUI

Resources mentioned in presentation
Monitoring Futures Survey – http://www.monitoringthefuture.org
Johnston, et. al. Monitoring the Future: A Continuing Study of American Youth (8th and 10th-Grade Surveys), 2016. Inter-University Consortium for Political and Social Research (ICPSR 36799). – https://www.icpsr.umich.edu
Li, Arthur (2013) “A Tutorial on PROC LOGISTIC.” MWSUG Proceedings. – http://www.mwsug.org/proceedings/2013/RX/MWSUG-2013-RX08.pdf
Wayland, Jon. “What are the most in demand skills for Data Scientists in 2019?” Quora. Published 01/23/2019. Last accessed 07/01/2019 – https://www.quora.com/What-are-the-most-in-demand-skills-for-Data-Scientists-in-2019

Additional resources
View Proceedings – https://support.sas.com/content/dam/SAS/support/en/sas-global-forum-proceedings/2020/4853-2020.pdf
Resource Hub for Data Professionals – https://www.sas.com/sas/offers/resource-hub/roles/data-professional.html?utm_source=youtube.com&utm_medium=referral&utm_campaign=sgf-4406690&utm_content=rTyhgNFaUXE

Learn more about SAS Software
Free SAS Online Training – https://www.sas.com/en_us/training/offers/free-training.geo.html?utm_source=youtube.com&utm_medium=referral&utm_campaign=sgf-4406690&utm_content=rTyhgNFaUXE
Contact SAS® – https://www.sas.com/en_us/contact.geo.html?utm_source=youtube.com&utm_medium=referral&utm_campaign=sgf-4406690&utm_content=rTyhgNFaUXE
SUBSCRIBE TO THE SAS USERS YOUTUBE CHANNEL #SASUsers #LearnSAS #SASGF
https://www.youtube.com/SASUsers?sub_confirmation=1

ABOUT SAS
SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.

CONNECT WITH SAS
SAS ► https://www.sas.com
SAS Customer Support ► https://support.sas.com
SAS Communities ► https://communities.sas.com?utm_source=youtube.com&utm_medium=referral&utm_campaign=sgf-4406690
SAS Analytics Explorers ► https://explorers.sas.com/en/home.html?utm_source=youtube.com&utm_medium=referral&utm_campaign=sgf-4406690
Facebook ► https://www.facebook.com/SASsoftware
Twitter ► https://www.twitter.com/SASsoftware
LinkedIn ► https://www.linkedin.com/company/sas
Blogs ► https://blogs.sas.com
RSS ►https://www.sas.com/rss

Видео Multinomial Versus Ordinal: Does Model Selection Make a Difference? канала SAS Users