Understanding and Applying Factor Analysis in R

Подписаться 11 тыс.

Просмотров 21 тыс.

50% 1

===== Likes: 290 👍: Dislikes: 3 👎: 98.976% : Updated on 01-21-2023 11:57:17 EST =====
Ever wonder what Factor Analysis is and how it compares with Principal Component Analysis? Look no further! This is a guide to further theoretical and applied understanding of Factor Analysis! This comes with a code demonstration in R.
Forgot what Principal Components is?
• Applied Principal Comp...
Check out how to compute factor scores!
www.real-statistics.com/multi...
Data
www.openml.org/d/509
0:00 - What is Factor Analysis?
1:42 - Terms to know when using Factor Analysis
4:09 - Set up Code and Model decision
7:05 - Interpreting Factor Analysis Output
10:45 - h2 and u2 interpretations
12:28 - Complexity term interpretation
12:49 - Other statistical measurements

Наука

Опубликовано:

14 июл 2024

Ссылка:

Скачать:

Готовим ссылку...

Добавить в:

Мой плейлист

Посмотреть позже

Комментарии : 34

@shaimaadoma 2 года назад

Thank you, that was very helpful! ^^

@recordyao 3 года назад

Good work!

@aditiawasthi4900 3 года назад

Very nicely explained

@alonsomadronal2919 2 года назад

Excelent video! Keep up with the good work, you are helping a lot of distressed students!

@pakwidi531 Год назад

Ah thank you so much sir 🙏

@gorraf70 2 года назад

thanks so much...I'm working on my thesis and this was extremely helpful... 🙃

@0banana751 2 года назад

목소리가 너무 매력적이에요! 우와

@FleurChelsea 2 года назад

Thank you for this video! Do you have any suggestions on how to handle missing data in factor analysis?

@SpencerPaoHere 2 года назад

I have just the video for you :) (data imputations) ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-MpnxwNXGV-E.html

@nataliaesquenazi7280 2 месяца назад

After factor analysis, how we can create an index or indicator?

@sumbomarcus 3 года назад

His voice

@VISHESHKULSHRESHTHA3 2 года назад

how to use output of factor analysis output/factors in clustering or other ML algo like classification?

@SpencerPaoHere 2 года назад

Great question! Until I do a topic on Factor Analysis Regression (FCR), you can take a look at this video: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-H45NWCzIDkY.html (I go over the logic on how to use the transforms for other modeling procedures -- its the same process)

@TheBlomb. 2 года назад

How do you know the # of factors that you look for? Is this based from your research context, or can you read the is from the date by experimenting with more or less factors? & what if you have contrasting factor loadings, can you invert these? (I.E.: I have question on how challenging something is, and after how easy it is which is in contrast)

@SpencerPaoHere 2 года назад

I arbitrarily stated that the number of factors be 3 in this video. However, a more "scientific" way of determining number of factors is either 1) using a scree plot (elbow method) or you can check out this paper here: ruscio.pages.tcnj.edu/files/2016/08/Ruscio-Roche-2012-PA-Factor-Analysis.pdf on a more mathy way of finding out number of factors to optimize for. (factor loadings) You can also attempt to gridsearch for the number of factors (brute force based on model results) I'm not sure what you mean by contrasting loading factors?

@TheBlomb. 2 года назад

@@SpencerPaoHere Thank you for your response and the source. By contrasting factors I meant, variables, and I have solved the problem by inverting them. It should be sorted. With regards to the factor loading, after some reading, I used a parallel analysis to determine I need two factors. The new problem now is that the FA model does not satisfy RSMEA 0.9. I only achieve the satisfaction of those two requirements when I use 4 factors. What would be the best to listen to, the parallel analysis or adding/removing factors until the FA model makes sense w.r.t. RSMEA & Tucker's. Thanks again for your input, very much appreciated.

@SpencerPaoHere 2 года назад

@@TheBlomb. Haha yeah. Regarding which "better" method to use, I'd defer to the testing data. If there is a better "score" of some sorts, I'd more or less default to that specific method. However, if you want to avoid the black box algorithm output, and assuming they both have similar results, I'd go with the method that has the most explanatory power. Could you do some additional analysis and try and determine what the factors might represent your original features and determine if the representations make sense?

@intentionallivingph7279 2 года назад

Do you have a video explaining Tucker’s? Thanks

@SpencerPaoHere 2 года назад

Hmm I do not. I am not even sure what Tucker's is haha. Sounds very niche.

@ramziraspaty6854 Год назад

I have a question. So, you arbitrarily stated the number of factors you used in this video and you said that a more 'scientific' way of determining numbers of factors could be done by using scree plot (elbow method). You know that some data don't have a good scree plot diagram, right? If that's the case, can I use like the Eigenvalue thing? Thank you so much!

@SpencerPaoHere Год назад

Yes! You can use just the eigenvalues to determine if you want to keep X features. If the eigenvalue < 1 can be eliminated. However, this approach is more appropriate for smaller models and can restrict larger models.

@ramziraspaty6854 Год назад

@@SpencerPaoHere Ah now I get it. THANK YOU SO MUCH! My lecturer had given me this material but I didn't get a single thing she said T_T

@tomthomas9138 Год назад

while applying the pa and ml method the values for the h2 and u2 is not showing and also i have 10 variables but for 3 factors the cumulative variance is 0.43. so what to do?

@SpencerPaoHere Год назад

What is the variance explained with you add up the 4th factor? Also, you might have NaN values in your dataset which may have led to not having any h2 and u2 values? (speculating)

@jaelee6093 3 года назад

Why would you consider absolute BIC values only? Whether the values are positive or negative, you should consider the model that gives you smaller BIC: see en.wikipedia.org/wiki/Bayesian_information_criterion. Please let me know if I misunderstood anything and thanks in advance for your input. And thanks for the great tutorial.

@SpencerPaoHere 3 года назад

Great question! Sometimes, you have negative BIC values. You'd want to take the absolute value of these values to have an 'objective' valuation of this model with other models that you have. If you have a -inf BIC value.. this is as 'bad' as a +inf value.

@Mayorex_21 2 года назад

My analysis for factor analysis is returning NA- not available

@SpencerPaoHere 2 года назад

How can I help?

@gaoelnlaojehc8913 3 года назад

where did u learn bro?

@SpencerPaoHere 3 года назад

The internet :P

@gaoelnlaojehc8913 3 года назад

@@SpencerPaoHere Any specific sites or blogs sir? BTW I like ur vids man... pls continue

@SpencerPaoHere 3 года назад

@@gaoelnlaojehc8913 I appreciate your kind words. :) I usually start off at .edu websites. Stanford has a lot of great theory related to ML. Medium articles have application oriented scripts that can hammer home understanding. And, of course there is stack overflow.

@gaoelnlaojehc8913 3 года назад

@@SpencerPaoHere Thanks man. Appreciate it