Introduction to Survival Analysis [1/8]

[@OwenMcKinley]

The best Statistics instructor online, right here. Your content is appreciated, Justin! Thank you 😊😊

[@luisaugusto1337]

And he's back with perfect teaching!

[@manishkumawat2350]

The reason i seek for, i always find them in your video. My love from India.

[@IAmShadrackKibet]

This came just the right time! when I am getting started to learn about survival analysis. Looking forward to more. What a great explanation Justin. Thanks

[@makemymarket1772]

I rarely comment videos, but you helped me through stat II and now stat III. THANKS a lot for your videos, you are a hero.

[@abhirupmoitra8711]

Sir the way you're explaining , I'm understanding survival analysis more precisely.

[@AhmedGadd]

It is very simple to capture the idea. From a starting time, you monitor when an event occurs [based on a number of samples] and then analyze the time taken. This analysis helps to predict the estimated time for this certain event to occur in the future for new cases. Really than you!

[@irfanshakeer1373]

I have been eagerly waiting for this. I had even requested this topic. It's not an easy topic everyone can just explain. Hats off to your work. Concepts go in our heads really quick and organized when you teach.

[@bo-bx5hn]

I just started looking into this for and industrial application. This series may save me a boat load of reading, so thank you in advance.

[@mahfuzulhaquenayeem675]

That was so easy to understand! Thanks a lot for this creation.

[@mitheomuranga4747]

Thank you sir for making this videos available. They are very clear and easy to understand. Thank you so much for your sacrifice. May God bless you.

[@mahmoudelmaghraby1548]

Thank you. Please complete the survival series. I have been waiting for months

[@donwhitejr.5901]

I enjoy your videos. They are very clear and concise. I look forward to watching videos 4/8 through 8/8. You have the gift of teaching. Thanks for using it.

[@YogendraMhoprekar]

Because of you I start to enjoy Statistics. Thank you

[@festusboakye3698]

You're actually the best. Your explanations are clearly. But when should wait for the COX PH video

[@jieunsong4349]

Thank you so much for this very helpful content! You are such an incredible instructor. Just realized that 2/8 to 8/8 are not uploaded yet when I tried to find them after watching this piece. Looking forward to the rest of the series! Wishing you all the best :)

[@zedstatistics]

Thanks JS! Next few parts due Late Dec/Early jan!

[@lindaren9467]

Already a big fan. So glad to see that you made new videos about this topic. Now it is hopeful that I will manage this course. Thanks for your time and efforts!

[@viejozorrex]

Thank you for the content. There's a lot of information out there and, I think, for the nature of the topic, it's all soo boring. I found very easy to understand statics the way you teach it and I having a good time watching your videos. Thanks again

[@jaipb19]

Wonderful explanation. Eagerly waiting for other parts in survival analysis.

[@zedstatistics]

You can expect parts 2-5 certainly by end of Jan! Full time work makin it hard at the moment, but stay tuned!

[@subramaniannk3364]

@@zedstatistics Yes, eagerly looking forward! But, no pressure!

[@hasmikbeglaryan5086]

@@zedstatistics Justin are parts 3-5 posted? Cannot find them. These are so great. really helpful

[@Ankurkumar14680]

Very informative, it is considered to be a tough topic to understand but because of the amazing teaching skills of Justin....I am confident that we will understand it nicely. Request you to add few worked examples with the help of SPSS. Many thanks :)

[@zedstatistics]

Wait for the last vid where i do examples in all major software :) Will throw some examples into other vids too so dont worry!

[@elcapitano1633]

Cant wait to go on this ezciting journey! Thank you Justin

[@vikasvarma9299]

awaiting the next series of survival videos 🙂

[@forthrightgambitia1032]

Been wanting a series on this for a long time.

[@taladiv3415]

Great ability to explain concepts to the masses, as always! Thanks Zed :)

[@Tyhunzdawg]

we love you sir!!!!

[@clipslol]

facts

[@feurigerStern]

I am preparing for a project in Biostats and this is very helpful. Thank you!

[@narasimhacharys]

Superb presentation, good for layman crisp and clear..

[@matthewlueder2656]

WRT to covid-19, survival analysis actually is used for calulating vaccine efficacy. The moderna study uses a cox proportional hazards model.

[@ggoyadi9385]

What an amazing teaching skill, thank you.

[@ewanbarnett3859]

This is really great content. I'm doing using survival analysis for my thesis this year and found this to be a super helpful introduction.

[@RobinMario]

Great content, loose the dance moves!

[@imad_uddin]

This is really helpful. Many thanks

[@dineshmolavade4870]

Now I am going to learn survival analysis as well

[@khursheedstatistics5971]

We ndd pdf notes of ur lectures ..most kindness sir . Nd tysm fr the lectures ...

[@existentialrap521]

We out here movin up to survival analysis u know what it be. The whole hangs here gang’s here

[@harfir7169]

What happened to your videos on cox regression? Thanks for a great channel btw, you're saving my grades for sure x)

[@albertogubernati6677]

thanks for your passionate work, all videos are so clear and helpful 😃✌

[@khwajarahman8257]

Very informative, it is considered to be a tough topic to understand but because of the amazing teaching skills of Justin. iI am looking for rest of the video Survival Analysis [3/8] to [8/8]. please let me know how can i get those.

[@pauloszewierenko6978]

Very good explanation! Didactic a lot.

[@venusminervaliteral7476]

Hi, looking forward to the 5-8 series. thank you

[@DwaipayanDutta]

Great Explanation .. Thank you

[@pilot4500]

Very clear explanation! Thank you.

[@drak517]

You are the best teacher! Thanks

[@sophosalpha]

Wonderful presentation!. Thank you

[@ronaktiwari6127]

I'm a big fan of you Justin!

[@perseusgeorgiadis7821]

Not me studying for my biostats exam the day I'm gonna take it 😂

[@gretchenjannette]

Fantastic! Thank you🙏

[@abin_._antony]

4:07 If our aim is to just see if the patient would die or live, what should we use? Logistic Regression? Tests of association?

[@soukisama05]

Great video! I really enjoy your content!

[@sn5255]

Dude, create a course with all the formulas and some exercises and I will buy it.

[@chrismalone8470]

Hi Zed. Great video! Quick question: You said that survival analysis is not relevant to the study of COVID-19. However, couldn't we use survival analysis to work out how long it takes for symptoms to emerge after an individual is exposed to the virus? It also seems like we could use it to see how long people are infectious for after they develop symptoms or after they were exposed to the virus. Thanks!

[@nikhilgond600]

Sir please upload video on daily basis it helps us a lot and you explain it in a really nice way... please can you also do the analysis part using r software :)

[@nishaal98]

Hi, I really enjoyed the videos, where can I find parts 3-8 ? They have saved me a lot of time

[@pathakprathamesh]

Wonderfully explained! Would love to watch rest of the videos on your website but it seems to down currently?

[@Emily-Bo]

Very good teaching! Thank you!

[@mikefochtman7164]

So, with respect to period from diagnosis to event (death), how do we consider improved diagnostics? For example, some national program begins screening for lung cancers with a new test that detects it earlier, say one year sooner. On it's own, it obviously means the period from diagnosis to event is increased by one year just because we detect it earlier. But does early detection improve outcomes? It would seem that the period has to increase MORE than one year to warrant the new early screening program? Very interesting topic and you present things really well. Hope you have the time to finish the whole series, thank you.

[@luvannie8013]

This is great, Justin! I have a quick question if you don't mind. I'm thinking of using survival analysis for work to identify customers that have "high" prob of returning to a subscription business within 4 quarters. It's essentially the opposite of churn where we have accounts that have left but we want to identify the ones that might return and it's highly imbalanced. Just wondering if you think it's the appropriate application of survival analysis! Thank you :)

[@karannchew2534]

Another example, in marketing context: customer churn. When a customer stop using/buying/subscribing a service/product.

[@edbob3926]

Nice sir see you in science soon maybe

[@zedstatistics]

Lab coat lyfe

[@ChristinaBotros1]

Hi Justin, great video! Will the other parts to this series be coming out any time soon?

[@davodatesfawo5354]

Thank you for the video👍 I have one question thou. Can we apply it to "time to recovery?"

[@md.abulbasar7552]

amazing lecture thank you

[@chrisdaniels4446]

Hello @Zedstatistics how about we look at survival time for COVID 19 as the period of time human beings takes to adapt to the virus inform of immunity

[@guyle910]

Ayo what’s up J Z!

[@chhayakankariya2748]

Can you please make video Explaining Correlation and regression Realtionship?? And properties of regression.

[@v8pilot]

For me, survival analysis makes sense for covid ! How long between the first appearance of covid and my catching it...? Or my dying of it having been diagnosed with it....?

[@MusiXificati0n]

I find the survival curve and the question "how long until..." very familiar to geometric distributions. What is the difference between those two?

[@vijayarana8208]

very helpful

[@sulemanmustafa9704]

can anyone tell me, how to use the survival information provided in dataset ?And what can i do with it .Give me reference of research paper or website or anything.

[@randomvariablex1511]

I appreciate your content please can you explain whats reverse hazard rate and cumulative reverse hazard rate ?

[@DrFurb]

Nice and simple.

[@divutiful]

Hi, thank you for explaining the statistics topic in a very easy way. I would like to make a request that could you please make a video explaining i.i.d with example.

[@careymoses]

super helpful

[@SiyaMedia]

can the analysis be applied to sports? as in for example time for 2nd goal to be scored in a soccer match ?

[@SiyaMedia]

oh that was before i got to the soccer substitution bit

[@ahmedmo4801]

Thanks for your wonderful efforts. Any chance you can upload the other videos ASAP? I need them urgently!

[@zedstatistics]

Unfortunately full time work is making it tough, but I have some time over Dec-Jan where I'll be ripping through them.

[@ahmedmo4801]

@@zedstatistics No worries. Have you considered writing a book? I love your work and how it simplifies the concepts, yet thoroughly covers it, making it easy for us to digest. If not, can you recommend a good book/reference for the topics you covered in your videos, especially regression, in a similar interesting way (ie without going much into complicated mathematical details/proof of the theories)?

[@harrisrahman8660]

Awesome Video!! Please keep producing!!! Also where do I find parts 2-8?

[@zedstatistics]

Unfortunately you can only find them in the future. Still cooking them up - will post up once i get some time in Dec-Jan!

[@rahulmandalsky]

@@zedstatistics I am like so much waiting for it.

[@jochbo]

Thank you

[@nurfa2497]

Can we do survival analsysis for tuberculosis patient and loss to follow up ( default treatment )

[@TheGibberingGoblin]

thankyouu

[@Bydr-ei5nw]

Is this the same as survival models? Im wondering because i havent learnt it yet in my college

[@janz_snow]

May I just ask sir about one of your argument that survival analysis is more meaningful to use if we use it for disease that has delayed time onset of symptoms, such as cancer. Would you elaborate further this explanation as I am a bit confused if you are telling that delayed symptoms can be a tool to manage a more meaningful survival time?

[@zedstatistics]

The term "Survival Analysis" refers to an assessment of the time it takes for an event to occur after some exposure. It is of course useful to assess how many people survive say, a shark attack or catastrophic flood or a deadly virus.... but this would not be "Survival Analysis" for the purposes that statisticians refer to it. With shark attacks, catastrophic floods or deadly viruses, you either die really quickly, or you survive. You could come up with really simple statistics (percentages) showing how many people survive in these circumstances. But this is not "Survival analysis" per se. Survival analysis is the analysis of the time it takes someone to die after being exposed to some slower-acting disease or incident. Like cancer, hip-fracture etc. etc. It is a much more nuanced situation here that requires considerable thought (and a whole branch of statistics!)

[@janz_snow]

@@zedstatistics Such a very amazing explanation sir. A lot of thanks!

[@yordanosgizachew9356]

does video have a series?

[@derejetube1454]

do you have telegram website? how can i join you?

[@kasperbuskpedersen]

Nice!

[@adamatkins8496]

you have the looks of Jake Gyllenhaal and the brains of Sir Ronald Fisher

[@prasantskumarbisoi4066]

U r to handsome teacher ever

[@lonehegh8735]

missed my class so I hope and think you can help me on my way ;-D

[@boamahmarcus4002]

Wow

[@frrnxh]

so, where do I watch the next videos? 😅

[@andressanchezruiz7068]

Padre

[@fares5903]

Hey Justin .. thank you for this amazing video. Can you provide us a valid email to contact you please.

[@bo-bx5hn]

My bad for expecting the second video I guess.

[@mrpopulistless]

1 dislike. There are monsters that live among us..

[@zedstatistics]

Probably my mum trollin'.

[@AmosAiahKamandaTv]

Hi

[@JohnMartin-jx1wz]

Very odd view of how it applies to covid.

[@wolfganggoethe7810]

why?

[@JohnMartin-jx1wz]

@@wolfganggoethe7810 just because it does not apply to drug v placebo you cannot dismiss its isefulness out of hand. en.m.wikipedia.org/wiki/Proportional_hazards_model