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I don't think that is a rose.

Thanks John, your video helped me when I was about to lose! Thanks a lot!

I lost the data from the SPSS data file. How can we retrieve that?

If you have examples of binary outcome, please share link. Thank you!

thanks jon

Thank you!!

This video would have saved my dissertation! Only suggestion would have been to not use the “:” notation in the stack() command and instead show how to list out the stacked vectors instead (in case they aren’t ordered ideally in datasets)

Thanks! You explain this really well. Do you have any guides that can help build visualizations of interactions based on regression analyses? I have used some other guides, but the packages they use are not as amenable to customization as what you are doing here.

Thank you very much 🙏🏽

What a thoroughly intriguing video. Thank you for sharing.

Good video but that ambiance is stressing me out

I'm conducting survival analysis on solar flare eruptions and how long it takes their seps to reach our satellites. This video is excellent!

This is incredible, thank you

Thank you so much! But, unfortunately, I faced a problem while I change "random=~1|Sheep" with "random=~Week|Sheep", in my r script (following your pace), mod3<-lme(Gain_wk~Week,random=~Week|Sheep,data=Data1,method="ML"), it gives me a message " Error in lme.formula(Gain_wk ~ Week, random = ~Week | Sheep, data = Data1, : nlminb problem, convergence error code = 1 message = singular convergence (10)". I tried other 2 option , "mod3<-lme(Gain_wk~Week,random=~Week|Sheep,data=Data1,method="ML",control=list(msMaxIter=1000,msMaxEval=1000))" and "mod3<-lme(Gain_wk~Week,random=~Week|Sheep,data=Data1,method="ML",control=lmeControl(msMaxIter=1000,msMaxEval=1000))", it again messages me " Error in lme.formula(Gain_wk ~ Week, random = ~Week | Sheep, data = Data1, : nlminb problem, convergence error code = 1 message = singular convergence (7)". Would you please kindly help on these issues? Thank you!

Can I get the dataset?

Thank you very much. Great help for me!

thank you so much man, u goat

Excellent tutorial - Thank you very much. I get an error when I run mod3, as shown here Error in lme.formula(Job_Performance ~ 1, data = Data1, random = ~Days_of_Training | : nlminb problem, convergence error code = 1 message = iteration limit reached without convergence (10) I browsed the net and tried like this mod3 <- lme(Job_Performance~Days_of_Training,data=Data1,random= ~Days_of_Training|ID, method="ML", control =list(msMaxIter = 1000, msMaxEval = 1000)) But still, I get this error. for your guidance please

Is there any other way from the drop-down menu? I figured out another way by recording the missing value to be 0 and then running the compute command.

Very cool

Hi Jon, first thank you for the wonderful video! A question from me and I would really appreciate if you could help. What is the data type of the Job site, ID, Days_of_Training? are they <fct>, <fct>, <num>? I am actually confused with data type for multilevel modeling, My dataset has 4 columns, example: Countries <fct> levels: Australia, US, Thailand, Malaysia.. Status <fct> levels: Developed, Developing, Year <fct> : 2000, 2001, 2002, 2003, 2004 Life expectancy <dbl>: 87, 76, 69, 64 Should I just convert Year to numeric, and having 2000 as 0, 2001 as 1, 2002 as 2, 2004 as 4 ? Many thanks mate

the random slope model (mod3) also includes a fixed effects of time, why is that? couldn't I test a model with the random effect only or is that meaningless? Should I include both if it offers better fit than fixed effect only?

You saved my life, thank you sososososo much

Great video!! Thank you for explaining this!

I wonder how it differs using an an ANOVA test?

thank you very much!!

Very beautifully explained!!! Thank you sir!!!😇

Great! Thank you!!

Very helpful

YALLPH4GS BETTA SUBSCRIBE!!!

THIS SI MY REPORT. MY PROFESSOR DEMAND IT TO BE A 5 MINUTE REPORT.

Thank you so much for the video

very educating and summarises it all

struggling to find the numbers calculating ICC for mod3. Does anyone know where to find the two numbers in this video? the numbers are 1.2106302 and 0.6154547

Thank you

Thank you. It was really helpful

what if the response hase multiple answers. For instance, what if the answer to a question is option b,c,d?

Literally the tutorial I was looking for, thank you so much

im having an issue. I'm using dplyr to try to write this line playerb3 %>% group_by(tagged_pitch_type) %>% summarise(mean(as.numeric(rel_speed, na.rm = TRUE))) however since the column "rel_speed" has NULL values, the final mean reads NA. I dont want to simply omit the units though, I want to just overlook the NULL values. Is there a way I can do this while still using the "group_by" line?

eres un crack amigo. Realmente estaba sin saber cómo realizar esos gráficos de interacción en R y me has dado la mejor ayuda posible. Bendiciones

Thank You, Jon

Hi, these are great videos, quick question, if wanted to also fit a quadratic model, how would i do that? Thank you

Thank you very much for such a precise crash sourse on longitudinal modelling, forever grateful !

These are great tutorials!

It was a superb explanation! Thank you

amazing, thank you

I declare you the GOAT of MML. You helped me so much out with my master thesis and my first study to publish. Thank you!!!

Very interesting to know

Thank you so much! This videos help me a lot, this kind of models are hard to understand in a conceptual level, but step by step I'm starting to understanding it.

Interaction plot for 2 factor factorial experiment th-cam.com/video/En_k5ZNAfew/w-d-xo.html