Many thanks, Mic. Your thoughts and presentations are insightful and superb.
@christianaodimegwu31507 ай бұрын
Thanks immensely. Access to the resources makes it earlier to follow.
@ArranRWilliamson4 жыл бұрын
It fits and it all makes sense. I've been trying to work out which one to do and how to do it for days now, playing around with the ordinal regression to no avail. This one works, im running with it. MD thesis is done. Thank you, keep up the good work and goodnight. (the regret of not having given due consideration to the power of statistics, beyond basic interpretation, over the years is painfully palpable)
@mikecrowson24624 жыл бұрын
Hi there, Arran! Thanks for visiting and I'm glad this was useful with your thesis! (by the way, I do have a newer video on this topic from April in case you are interested): kzbin.info/www/bejne/bITCaWpuh82Ygpo) Good luck!
@bombabombanoktakom4 жыл бұрын
You are great! You don't know how beneficial your videos. Deeply thank you!
@lauratan43923 жыл бұрын
Thank you so much! You make my grad school life way easier.
@mikecrowson24623 жыл бұрын
Hi Jinny, thank you for your kind remark. I'm very glad you find my videos helpful! Cheers.
@elviedavid82506 ай бұрын
This is very helpful. Thank you.
@sintayehuhailu-v5x7 ай бұрын
thank you for nice explanation
@hannafalk5922 жыл бұрын
Thank you! You saved my day.
@mikecrowson24622 жыл бұрын
Glad I could help!
@jihanwidyacandra66413 жыл бұрын
good information for my bachelor thesis, thank you so much!
@huakbar43982 жыл бұрын
It's an incredible video. The explanation is better than a 5-star lecturer. Thanks so much for your contribution to education.
@mohammedlegas27403 жыл бұрын
its clearly informative vedio....thanks
@mikecrowson2462 Жыл бұрын
Please see my NEW 2023 video on multinomial logistic regression with categorical outcome variables here: kzbin.info/www/bejne/i3q9eYGKiNV4epo . You will also find downloadable resources under the video description!
@OfisLab3 жыл бұрын
great video Mike, really learned something, thank you!
@m1stylark5 ай бұрын
Hi Mike. I really, really need your help and advice. May i share my spss problem with you? i have this warning message : "Unexpected singularities in the Hessian matrix are encountered. This indicates that either some predictor variables should be excluded or some categories should be merged. The NOMREG procedure continues despite the above warning(s). Subsequent results shown are based on the last iteration. Validity of the model fit is uncertain'. I am not sure how to troubleshoot this Dr. I am a newbie. Google, youtube, researchgate and reddit could not help me =(
@ML-kc1we3 жыл бұрын
Thank you! It helps so much to understand and to interpret the multinomial logits models :) I do have a question: One of the assumptions is we should have independence of observations and the dependent variable should have mutually exclusive and exhaustive categories. According to my reading, it should be tested with the Haussman-Mcfadden (IIA test). But I don't think it faisable with SPSS, isn't it?
@learn50816 ай бұрын
Thanks for the video. Can't we compare non-reference outcomes? for example, "donald trump" vs. "did not vote"?
@ohudyansary2 жыл бұрын
thanks a lot, sir, how to adjust several variables into models and test the OR and CI .... ex (model 0ne blood pressure, age, gender. and model two contains model one + cholesterol, creatinine ,albumin )
@JCSTUDIOZ984 жыл бұрын
Just one question, could you use the Oaxaca decomposition with this method?
@shellythornton23473 жыл бұрын
Hi! How do we apply a Bonferroni correction to account for the family-wise error rate?
@mayumirufine78364 жыл бұрын
Thank you! This one helps a lot especially on the interpretation 💙
@ianaryan2333 жыл бұрын
I realize Im kind of off topic but does anyone know of a good website to watch newly released tv shows online ?
@billyshepard37863 жыл бұрын
@Ian Aryan Ehh atm i have been using flixportal. Just search on google for it :P -billy
@ianaryan2333 жыл бұрын
@Billy Shepard thanks, signed up and it seems like a nice service =) I really appreciate it!
@billyshepard37863 жыл бұрын
@Ian Aryan you are welcome =)
@franksogusa25142 жыл бұрын
You make it sound like these parameter estimates are done pairwise against the reference category. Is that correct though? I thought the estimated probability of the reference is just 1 - the sum of all other probability, so not 1 - the one probability we are just focussing on.
@Emily-ew6vs3 жыл бұрын
Thanks for this video!
@kleinbogen3 жыл бұрын
I have two questions: 1) How can I use the AIC and BIC info to help me in my analysis/model selection in addition to the p-values that you have shown here? 2) With the results from the analysis, how can I make a prediction on someone if know his/her gender, age, econlib and religious info? Thank you in advance!!!
@pravinraj59633 жыл бұрын
I am running multinominal logistic regression and the likelihood ratio (chi square) is insignificant, but the predictor is significant in the parameter estimates. Should i have to interpret them or i have to avoid them in my analysis?
@perksofbeingtheprophet93263 жыл бұрын
How would you write up these results in APA style? Thank you!
@polomarco12564 жыл бұрын
Hi! i have ordinal DV an i ran Ordinal Logistic regression but it didnt met proportional odds assumption then i ran Multimoninal Logistic regression but the model fitting information is not significant. what should i do?
@chancheeken98153 жыл бұрын
I have a question. If our Pearson and Deviance goodness-of-fit tests are significant (means the model is not a good fit) are we still able to use the data in the parameter estimates? Or will the data be not valid anymore? If yes, is there any solution to solve this?
@mikecrowson24624 жыл бұрын
NEW VIDEO ON MULTINOMIAL LOGISTIC REGRESSION WITH COVID-19 DATA DEMO: kzbin.info/www/bejne/bITCaWpuh82Ygpo
@gebreamlakgidey55134 жыл бұрын
Dear Mike Crowson. thank you for the nice and more interactive lecture. i found that, the video is more explanatory and like soft drink. what i want to ask for any one who are interesting is that' can we consider MLR for antenatal care visists??' becase WOH recommended than any pregnant mother must visit at least four times during the whole pregnancy ( Firist visit, second visit, third vist and four and above visits are the times). but to say adequate visits mothers must come four at least times during the whole pregnancy?
@Akshibhalla3 жыл бұрын
I didn't understand which variables go in the factor box and which go in covariant box. Why?
@Νελλη-ν9ξ Жыл бұрын
Do we check any assumptions before we do the test ?
@medhap80673 жыл бұрын
How I can use this for data where more than 1 response option has been chosen?
@luyaoliang6504 жыл бұрын
Thank you so much sir!
@davidngmenbelle69364 жыл бұрын
very educative. however, in this case how are you going to write the mathematical model or you need to write all the equations
@kleinbogen3 жыл бұрын
You said Male is 0 and Female is 1 but on the screen at the 2 minute mark, it shows genderid is 1 and 2. So which is the correct ID? Is 1 male and 2 female?
@refuge462 жыл бұрын
Great video. Thanks--I'm running multinomial regression on parent involvement with homework. Could you update the links? (Getting a Google error)
@mikecrowson24622 жыл бұрын
Hi there, thanks for your post. I have just updated them. They should be working now. Cheers!
@refuge462 жыл бұрын
@@mikecrowson2462 Thank you
@abdc82405 жыл бұрын
Hi, again Mike! I checked your video and thank you for your explanation of multinomial logistic regression (MNLR). Now the question I have is : MNLR assumes the independence of irrelevant alternatives. Most often McFadden test is used to check for that, my question is, how do you check that with STATA? Or do you just assume that this assumption holds?
@mesfinkebede23873 жыл бұрын
Yt
@ericah96755 жыл бұрын
Hi Mike, may I ask why you classified the categorical independent variables as covariates rather than factors? I had thought that covariates were for continuous variables and factors were for categorial variables.
@mikecrowson24625 жыл бұрын
Hi Erica, basically the categorical variable in this model was a binary predictor that was dummy coded. It was used in the same way that you would use a dummy coded predictor variable in the context of OLS regression. There's nothing mathematically "off" by doing it this way. If I'd treated "genderid" as a factor variable, I would've had to specified the reference/baseline category (an extra step or two) when going through the Factor route. But the results would've been exactly the same. My general preference is to use the Factors box for categorical variables that (a) have more than two categories and (b) would like the program to do the dummy coding for me. However, FYI, if chose to manually create dummy coded variables to reflect group membership on the factor variable, I could've included those in the Covariates box and accomplished the same thing. I just generally prefer to take the route with fewer steps if I already have a dummy coded variable I am using as a predictor. [Here is a video on dummy coding you might be interested in using OLS regression as an example, where I include factor variables in a model through the use of dummy coding: kzbin.info/www/bejne/jnjPk3qXhNiJb7c . I hope this helps!
@ericah96755 жыл бұрын
@@mikecrowson2462 Thank you very much, Mike! And sorry for the delay; I didn't receive a notification for your reply.
@mikecrowson24625 жыл бұрын
@@ericah9675 No worries. I hope you have a great day!
@maikandir4 жыл бұрын
God bless!
@lilianazer34773 жыл бұрын
If gender was significant how would you interpret that without setting a reference group?
@mikecrowson24623 жыл бұрын
Hi there. It's been awhile since I put this presentation together, so I am not entirely sure what you are referencing. However, I have a newer presentation on multinomial LR that I put together last April that may answer your question. The KZbin video is found at: kzbin.info/www/bejne/bITCaWpuh82Ygpo I also have a Powerpoint (that accompanies the video) that provides a much deeper dive on intepretation at: drive.google.com/file/d/1nKkBGrM90yRbo7ErvWe8ZxT_qiQAdgMo/view I hope this helps!