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This was a really good video

Thankyou for a clear explanation.

10:00

Thank you very much for this explanation, You are brilliant and very good mentor

Great job thanks

super hilfreiche videos!! warum muss die reihenfolge der pararmeter auch anders sein im englischen :((( hätte mir so viel zeit und frust sparen können wenn ich das früher gewusste hätte! (ich hoffe, dass es so ist und ich das jetzt durchschaut habe haha)

Very good presentation. Thanks

Very effective approach to understand for beginners, Thank You! From 🇧🇩

Thanks, A great Teacher

Wow something wired just happend I swear I was trying to listen to your lecture about this topic previously but wasn't quite able to grasp it, now its like very clear to me. Thank you for your work, I think thanks to you I am starting to see this statistical modeling picture now.

short and sweet

Me after the 5th video... Already feeling like a statistics guru

great explanation... Thanks

An excellent lesson thank you Christoph

thank you Christoph so much

Awesome job man! This is good stuff, thank you for this!!

Great content.

Hello, I am French and it is a true pleasure to follow such clear explanation on this subject. Thank you a hundred times ! And congratulations. You present very well

There are many great researchers and their works on line. Their researches have been helpful. kudos to everyone.

Now is the analysis is trending, maybe you should start posting again

Hi Christoph. Thank you very much for your very clear tutorial. I particularly like your combined use of code and handwriting to demonstrate the methods! I am relatively new to R and am currently using categorical variables (more than 2 levels in each) in a meta-regression model (using the robu() function in R to implement robust variance estimation), to investigate their individual effects on the combined effect size generated by the meta-analysis. I am using an existing article as a guide (Shields et al.,2017 - The Effects of Acute Stress on Episodic Memory: A Meta-Analysis and Integrative Review), where the authors seem to have used contrast-coding for a comparison between each level/category and the grand mean (rather than comparing between levels or with a default reference). Sum (or deviant) coding appears to achieve this; however, I am always unable to report the coefficient and associated p-level for the 'dummy/reference' level that gets dropped due to k-1 columns. I wondered if you might know a way around this please? Maybe by creating a bespoke contrast? I will keep hunting, but yet to find a solution! Many thanks, Lucy.

Could you explain how to get the method of moments estimator for the compound poisson process?

Simple! Very good for people like me (1º stepts on R). Thank you Christoph!

Nice explanation..Christoph.. Can you suggest the use of mixed linear models for a unbalanced data.. varieties of three different maturities like early, medium and late that are variable across the years (few being common across years)? How to proceed in such case? Any suggestions please

hello, thank you for this video. i have a question... when use a particular distribuition on the model? like poisson or gama?

Dear Sir, Greetings. I am Rabiul from Bangladesh. I am doing my PhD, I have done my analysis on the basis of your video. I have 2 treatments (open and bagged pollination) and I have 4 sites as replication (edge and centre) and 4 locations. I need the value of (df, f, and p) of seeds/pods, 1000 seed weight and plant yield. But I am not able to understand it. Would you please help me. Kind regards, Rabiul

what about beta2??

For proportions data, can we use logistic regression??

Such a wonderful presentation 😊😊

Sorry, I believe your interpretations are a bit... misleading. At 16:33, you write that "In a glm, an individual slope gives an estimate of the multiplicative change in the response variable.... ". This is not always the case. This is the case for the Poisson distribution because the default link is a log link. But, you could easily run a glm with a Gaussian distribution and identity link, which would have an additive interpretation. Further, it is best practices to indicate your link, even when the default is intended (learned that the hard way :) ).

This has given me problems for years, this is super helpful.

very helpful and clear style! would be good to have a followup video about how to visualize the data with this sort of model.

Hi, this video is so good and useful for me, I have a question, in the result of this model on my data , residual plot shows is not fitt( the distribution of oats is not looking like the star in the sky), who do I improve it? is there any reference? so thanks mahnaz

Thanks Chistoph for the great explanation. 1. In this model how can we check the accuracy of the model when we have test data with us. 2. Can we apply other non linear , tree based and other ensemble models too

You are very good in explanation. Everything is clear. The speed is convenient and the content well-addressed. Thank you very much!

THX Chris, Gr8 video :)

perfect... thanx

thanks a lot for your time and clear explanation is was priceless, I hope you can share more videos :) I'm looking forward to GLM part 2

Are you able to make the 6 plots because the database is structured in such a way that R intuitively knows that which variables are nested? Can a flat dataframe give you this as well?

Muchas gracias por el video. Me fue de mucha utilidad.

A very good presentation. I loved it :)

What hell do you do next? How come nobody ever tells you how to interpret the models?

Thank you very much !

Hey Christoph, is there any hope for a next video?

Many thanks for your invaluable information and explanation about the regression modeling. Could you please provide a bit more information for us. Best Regards

A quite helpfull video.

I wish I'd seen this video last month. Better late than never. Subscribed!

Danke sehr. Es war sehr Hilfsreich....

Thank you. I had no success learning R and have tried for months. I stumbled on to your video and I learn to run names after I load a data set. How simple. Now I am off and running.

How can you tell that the relationship is not linear from looking at the plot?