Forward, backward, and hierarchical binary logistic regression in SPSS
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- Опубликовано: 9 май 2018
- This video provides a demonstration of several variable selection procedures in the context of binary logistic regression. I begin by discussing the concept of nested models and then move to a presentation on how to carry out and interpret models where variables are entered using either an empirical approach (i.e., forward and backward) or a hierarchical approach (i.e., based on the researcher's conceptual frame). A copy of the data can be downloaded here: drive.google.com/open?id=1p1H...
For more instructional videos and other materials on various statistics topics, be sure to my webpages at the links below:
Introductory statistics:
sites.google.com/view/statist...
Multivariate statistics:
sites.google.com/view/statist...
A comprehensive video on variable selection in regression. Well explained
Excellent video - clear explanations and easy to follow. Great job Mike!
Hello Mike. I have been following you video tutorials for quite some time now. This particular one makes me feel statistically moved... and it is significant if you ask. Thanks for sharing. I have learnt a lot from you.
This video is nice explains and builds up the concept. Its really helpful. Thank you.
This is very useful demonstration. Thanks for sharing
Thank you! This is so informative and helpful.
Very informative! thank you very much!
Thank you so much! This is so helpful!
Very nice video, thank you.
Thank you so much! Your lecture is clear and helpful.
Hi Wendy, thank you very much. By the way, I have a video from last February that I put together or hierarchical multiple regression at ruclips.net/video/RyDteu6E7HY/видео.html
You can also download a Powerpoint and the data to play with by following the link under the video description, which you might find helpful. Cheers.
Amazing work! Thank you!
Legend. Thank you.
Thank you for this very helpful video! I have a question -- I ran a forward stepwise binary logistic regression with 5 possible variables. I ended up with 3 out of the 5 variables included in the model. The model was significant compared to step 2 and compared to the null model; however, in the "Variables in the Equation" table, step 3 shows one of the variables in the model to be insignificant, while the other two are. How do I interpret this?
Thank you Dear. GOD bless you. You explained it very well, Do you any more material regarding logistic hierarchical regression.
Hi, i am testing 11 independent variables for binary regression analysis, following your explained method of variable selection when i am applying Forward LR method only Block 0 appears ? could you please explain why? (note the backward option is working as u explained) thanks
Good job and well done; I'm sure you're aware and probably sick of hearing it by now but one of those pen pads would be a big improvement for adding the handwritten text - one that can keep both the pen pad and the mouse going at the same time.
Dear Mike, thank you for the informative video. Can I ask what are the steps if I want to perform forward, backward or stepwise multinomial logistic regression since my dependent categorical variable has more than 2 groups?
Thanks Mike for the good explanation, I got a question: what if the homsmer and lemeshow test is significant for the first model?? I got 2 models in total
Hi Desiree. When you say "significant for the first model", do you mean the first of two hierarchically-organized models (where the first model contains a subset of predictors relative to a second model)? If that's the case (and the second HL test is not significant for the second model), then I assume that the addition of predictors in the second model yielded an improvement in fit. By the way, in case you might be interested, I have a 2019 video on logistic regression as well (ruclips.net/video/cpWSSJHuT2s/видео.html). Cheers!
@@mikecrowson2462 Yes Mike. I got a 3 step hierarchical model and the first model with only non-modifiable factors is not calibrated (HL test significant).. while with the modifiable factors added in step 2, HL test becomes not significant..can I say that only non-modifiable factors are not adequate in predicting my outcome variable? Thanks so much for your response!
@@mikecrowson2462
Nice one
excellent
I have a similar situation as Kyla below, any suggestion?
Hey Mike.
If we have nominal and scale predictor variables, can we add all those simulataneously as you have shown or is there any other method available for that?
Hi Neha, thanks for your email. If you have nominal or ordinal variables as two levels (i.e., they are binary), then you can add them in this way. If you have categorical variables with more than two levels, you'll need to recode them into a set of dummy or effect coded variables. I talk about dummy coding here (ruclips.net/video/XGlbGaOsV9U/видео.html) and effect coding here (ruclips.net/video/Kse6t-a9s2U/видео.html). Also, just an FYI, you might check out two new videos I put together on the topic from this video: ruclips.net/video/RyDteu6E7HY/видео.html and ruclips.net/video/lLsIanDaKRw/видео.html . Cheers!
@@mikecrowson2462 those are linear regressions that I understand. But if we want to do backward stepwise logistic regression for suppose 3 categorical and 5 scale predictor variables with categorical (having 2 values) dependent variable, then how to add those all predictors in one model?
Or we have to put them separately in block 1 and block 2 respectively.