Interpreting SPSS Output for Factor Analysis 

I am in the final year of my PhD and I have used SPSS throughout without any formal training apart from watching your videos. You are the best teacher ever. You are just too phenomenal. You have been a great teacher to some of us low income countries.

you're currently saving my academic life, so thank-you!

This video really saved me from depression, I was struggling to understand so far. A great teaching method. Thanks, Dr. Todd

I am a PhD student in Epidemiology. My professor just asked me to do factor analysis and I had zero knowledge about this analysis. Your video helped me a lot. Thank you so much.

You are a God sent. I am doing Statistics II and have no clue but through prayer and your videos, I have been getting A's and B's. Thank you.

You explain everything in a nice manner, no redundant talking as there are in many other videos on youtube. Although I appreciate any effort made, it is really great to watch a video explaining concepts in detail and also being up to the point. Thank you so much!

Thank you, my whole semester is clearly explained there and I´m finally get it! I am very grateful.

Great explanation. Way better than my tutors. Please make more of these. You are helping and, reading from the comments, saving a lot of students. as for a comment, It would be nice if you also explained more to WHY you want or need certain numbers it would explain a lot too. KR. Floris

You are the one getting me through my masters degree.

Dr. Grande, you even have SPSS tutorials? Who’s better than you?! NO ONE💖

Thank you so so much you saved my thesis,I didnt knew what to do . after watching this video I was able to complete my report. So again a big thank you .

Thanks Dr. Grande, great explanation and very easy to follow. I'm about to take an exam on principal components analysis and canonical correlations.

Great tip about using orthogonal rotation when there is no factor correlation > |0.32|. I was reading Tabachnick and Fidell (2007) and came across similar advice about the factor correlation matrix (p. 646).

Very well explained. Thank you Sir.

This video was so helpful for the beginners. Thank u so much.. But I have a doubt regarding choosing the rotation type. Can u plz explain me?

Very simple and to the point! Thank you!

Thank's a lot for Dr.Todd your tutorial for that topic so helpfull .....

Thanks you Dr Grande. Awesome videos, helping me a lot!

Thank you for this amazing video. Everything is more make sense now

I just have a question, why we should we have a value of 0.32 or greater in the Component Correlation matrix to choose the Varimax rotation type?, why it is not 0.3 or other values?? is there any source mentioned that?

Very nice explanation. Thankyou so much.

who wanna learn factor analysis should watch this

This has just been so much help to me. Thank you.

the video just helped alot. the way of explaining and demonstration is really great. Thank you

Thank you so much. It would be better to attach the description of assumptions for each table and their significant values.

Clearly an older version of SPSS since that Factor dialogue box looks different in current version. The last part of the video you mention the 0.3 as a threshold for factors and how they were grouped by type. I wish you had spent another 10-20 seconds and elaborated on that a little bit, what that implies exactly. Overall good video and thank you.

Dr. Grande , thank you so much !

Thank you so much professor. You really help me

Briliant as always!

Thank you next, Dr. Grande !!!

great explanation, thanks Todd

Excellent and so clear! Thank you

i loved your video, it was very informative but i have one difficulty. Does it matter whether the factor loading value is negative or positive or do they both have the weightage. Should we prefer the smaller but positive value such as (0.22) over higher negative value such as (-0.89) when collapsing the variables into factors. Please provide ans to my question

Hi Todd I have two questions. Using different rotations methods, how could you know which one is the best one? component matrix is the loading matrix, isnt it? Thank you very much for your help!

Thank you Sir for the explanation. Sorry i am a little bit confused. I want to do factor analysis precisely CFA for my work, but i don't know if the steps you follow on the video are the same even for EFA or CFA

Thanks for ur clarification

Another masterpiece, thank you.

Dr.Grand, I have some problem in EFA. There are 9 components whicha has eigen value more than one and various items are left with factor loading less than .6 Please help me what to do. KMO is .761 and there is no high correlation above 0.7

Thank you It very helpful

Thank you for the helpful video. Two follow-up questions. (1) I read elsewhere the suggestion that the item should be removed if the extraction value (in the Communalities table) is < 0.20. That seems to make sense because too little variance is being explained. Do you agree with this approach? (2) What would you recommend in dealing with items that cross-load across multiple factors in an exploratory factor analysis? Thanks in advance!

Sir nice explanation.. How to write hypothesis for the above problem And how to analyse the output.. Relating to hypothesis

Hi Professor Todd. Thank you for the video. It was really very helpful for a beginner like me. A quick question- when we analyze the component Transformation matrix (under direct oblimin) and in the output table we have 2-3 variables whoes value is greater than 0.32, do we still need to change the rotation type to varmax or continue with the old output?? I tried displaying the data with both the rotation types and they are different. What do you suggest??

What is the formal interpretation of having factors load together of it does not mean that the factors are perceived to be measuring same latent variable? or loading together should mean what?

Hello, Thanks so much for this video! I hope you see this question :) I used direct oblimin and Varimax and had absolute values over .32 in both. How do I decide which to stick with? PS: I am doing a factor reduction for over 100 items and both solutions reduced my items to 25. Also my N = 123

Thank you Dr Grande, Please I would like to know if it is allowed to use the component matrix instead of the rotated component matrix?

found this very helpful. I get the interpretation now. Thank you

Thanks, very helpful!

Thanks Dr Todd for your very informative videos on Factor Analysis. One question: I notice that the Determinant value for the above Correlation Matrix is 3.81E-5, which to me is 0.0000381 which is less than the thresh-hold value of 0.0001 below which Factor Analysis is not recommended due to high Collinearity, as quoted by various people. Is my understanding incorrect? Thanks again.

How do you tell a test is unidimensional or multidimensional? Help please!

i want to ask when you select rotation methodf from obliman to verimax you say 0.32 vlauewhat it means where it comes from

What does the percentage variance explains? And how much variance is good for the dimensions?

dear dr, is there any extraction value that shows problematic commonalities in factor analysis? you said that higher values are better.. right? what low value would be considered bad?

What should we do if there is negative factor loading Sir? Should we keep that item or not? Thank you 🙏

great video and explanations

it's very great to learn. I have one question that if I have scores above the .3 on two factors then which and how we can consider that the item xx is on which factor or should be on which factor. thank you

You are saying: if it is greater than 0.32 (what in this case it is), i would stick to oblimin. But why do you chose for VARMIAX??

I have a large number of scale items and I need to narrow it down to factors in order to test the hypothesis, so I used factor analysis, I noticed that I can have 3 component, however 1 component when I ran the reliability test for it it was very low (0.4) it is understandable since it only has 2 items, I can't use it because of this. I decided to do what you did as in limit the components to 2 and in the transformation matrix the first component is 0.682 (correlated, I think the word?) with the second, while the second is the negative of that number (-0.682) with the first component and with each other 1 with 1 and 2 with 2 (0.731). Are the values acceptable and can I continue using 2 components? if yes, then how would I interpret the results in my thesis about the component transformation matrix (the one I just mentioned its values) and the total variance explained table (since it shows 3 component not 2)

Thank you for this videos. I have a question, how I can get the index of fit (chi-squared, RMSEA, CFI) in SPSS?

What is the most important value like p value in factor analysis?

Please answer, how to find relationship of factors with dependent variable

how i can get reproduced correlation matrix? how i can calculate standard deviation of residuals ? thanks

Thank you Dr. Grande!

Why .32 sir? Thank you so much for this.

The level of dissonance I experienced when your true crime video was playing on my tv and this video started playing on my computer as I'm tinkering with spss XD

Great video, Tks very much!

Hello Dr. The video is very helpful and a good guide. Would you share your data for practice?

Thank you very much for the video Dr. TL Todd. I did not however get the point of 'mixture of positive and negative correlation matrix' right. Again you mentioned for symmetrical data SPSS give a KMO value of 0.5 hence your rejection of value as suggestive of appropriate factor. My question is is this true for other softwares? Thank you

Very difficult....

How do I know what questions each component is in the "Total variance explained" table?

Thank you for your video. I am wondering how do we get chi square value?

What are the differences and implications for extracting factors based on eigenvalues greater than 1 versus using a fixed number of factors to extract while using PAF on spss? Or, do you have any literature that can point me in the right direction? I want to extract a relevant factor for my theory, and when I run my items on spss, using PROMAX, PAF-extraction based on eigenvalues greater than 1, more than one factor extracts from the factor matrix. In prior instances this has happened; even with decent loadings above .500. Is it possible to use a "fixed number of factors to extract," ask SPSS to extract 1 factor only if I can rationalize it through the literature?

Thank you, it was so helpful.

Sir what if we get negative values for a component in rotated component matrix?

Dr. Todd shall we consider extraction value below 0.5 on communalities table or remove it for further factor loading process? Please help.

How do you know if certain components didn't load?

Respected Sir, Is data normality a necessary condition for running EFA?

how to determine the significant value of PCA?

Hi , I'm having an issue with combining my questions into 1 and the test the correlation. Should I follow factor analysis method you have shown above or go with computing under transform tab.

Hii, How the factors are saved in the dataset?. Which outcomes contribute to that?

I am doing PCA on assets of rural farmers of South Asia. Based on factor loadings on 2-3 different principal components how can we classify them into Poor , Medium and Rich farmers ??

I am not even sure you are going to reply but here goes nothing, I am currently doing my dissertation and my first step on my to do list was to do conduct a factor analysis hoping it would result into three categories but instead it produced over 5 factors so what should I do?

Thank you! Very helpful

Hi Todd, How can i calculate individual case scores following a principal component analysis? kindly help

Thank you. I applied factor analysis to data from an employee engagement study and identified 2 factors. How will this result assist me further in identifying and prioritizing interventions?

How can the combined eigenvalues of a set of variables which are closely related be ascertain?

THank you Dr TOdd! I really understant all easily, what I was looking for! One question please, what is the minumum&maxumum Absolute value below in Options?

Can I apply this method to create an index of 10 variables with different scoring procedure

Is it possible to do factor analysis with yes or no questions?

thats really helpful ..

Hi, I have a question. I'm testing a model with 3 variables (2 DV, 1 IV). But 1 DV and the IV load onto the same factor since the answers were so similar (Quality of something and the trust). Is this a problem? How should i mention this in my findings. Thanks for all your great videos!

is there any way on how to extract less components in rotated component matrix?

sen kocaman bir kralsın

Hey Todd, thank you for this great video! I Just have one question: is this a confirmatory or a exploratory factor analysis? Thank you in advance and best regards, Andrea

Dr your are a saint

Hi Prof. Thanks a lot for your wonderful lecture. I just have one quick question: Is the extraction value for variables the same as what is known as Factor loading?

I have been watching your videos and they have been such a great help! However, I have one doubt. My determinant is actually smaller than 0.00001. How can I proceed? :/

Hi Dr Todd I am still struggling to find unidimensionality through factor analysis. I have been reading a lot of articles and more I am reading more confusing it is getting

Hello , i have one question, how can i reextract the component again after we extract at the first time ?

Do after second order factor analysis.. % of variance changes of factors?

Please help me to improve my KMO Test results , it is coming less than .5