By the way, my stat course will start in EdX on January 19th. Slides and datasets I use in EdX will be available for public use. I hope you check it out!!!
Very clear tutorial and fluent English. It would be more practical if you could attach the data set together so that we can try on it while listening to your explanation. Thank you
Hi, Ayumi, thank you for the great video! I have a question, do you know how to create the K-M curves adjusting for the time of heart transplant? In the next video, you only show how to conduct time-varying Cox regression, but what if I want to create a K-M curves after adjusting for the time of heart transplant like the one showed in your video? Could you help me with it? Thank you so much!
I intend to analyse survival analysis for companies. If I have to run cox regression for the same set of companies for 10 years, is the procedure same in spss. How do I go about. The same set of variables are studied, but the values of these variables change. Kindly help me as I am stuck.
Dear Ayumi, Thank you for your video. I have a (naive ?) question regarding the Cox model, particularly about one covariate, measured only at baseline ... As this covariate is related with the severity of a medical condition, I can assume this covariate can change over the time, but I don't have any follow-up data for it ... So here is my question : do you think it is relevant to put a baseline value as covariate in the Cox model to predict an event related to this condition ? Thanks a lot for your answer. Kind regards
Hi Ayumi, may I ask if it is possible to do a prediction from time varying survival model to a new dataset? if yes, how should we prepare the dataset for prediction? Thanks in advance, any opinion still help (y)
@@ayumishintani7044 hi ayumi, thank you for your time. Is that the construction is for training the model? If that so, I think I already getting to understand how to construct the dataset for training. What I mean was what if we have trained the model and want to use the model to do a prediction for new dataset? Do we have to set the construction of dataset the same as we prepare it for training but without censor/event status? Thank you before, i am curious about if after i modeled the survival analysis, is it possible to predict with new dataset whether a unique ID will reach event or not and when will it happen, just like logistic regression concept of predicting probability but no timing prediction. Pardon me on my grammar 😁
@@randylawrentius9760 Computing predicted probability in Cox regression for validation dataset is much more difficult than that for logistics regression. Logistic regression has an intercept in the model, Cox regression does not. Cox regression instead has baseline hazards which is non-parametric. You need to consider baseline hazard in the prediction in the Cox regression. You can use the baseline hazards from the training dataset, or can update baseline hazard from the validation dataset with beta-coeff from the training dataset. In the later case, you should fit data from the validation dataset with censoring variable and borrow the baseline hazard from the validation dataset analysis while bata-coef from the training dataset-analysis.
This is a fantastic tutorial! Thank you, Ayumi!
I am glad that you liked my lectures. The slides and datasets are not available in public yet, but I will see what I can do.
Was the dataset ever made public?
By the way, my stat course will start in EdX on January 19th. Slides and datasets I use in EdX will be available for public use. I hope you check it out!!!
Ayumi, this is an outstanding explanation!
Very clear tutorial and fluent English. It would be more practical if you could attach the data set together so that we can try on it while listening to your explanation. Thank you
hasyashah Thank you! I am planning to present my course in edX this year, in my edX course I can share example datasets.
Thank you very much for your tutorial. Help me a lot for my paper.
Hi, very useful video...could you tell how to generate the event history graph that you show?
Thank you this useful tutotial
Hello,
Thanks for this video, very clear, I really liked it.
Can I access this slides and the databese for university work? Thank you
Hi, Ayumi, thank you for the great video! I have a question, do you know how to create the K-M curves adjusting for the time of heart transplant? In the next video, you only show how to conduct time-varying Cox regression, but what if I want to create a K-M curves after adjusting for the time of heart transplant like the one showed in your video? Could you help me with it? Thank you so much!
Yes I have this in Japanese video.
Will try to make it in English
Please see this video ua-cam.com/video/Lbqdvn7YHh4/v-deo.html&vl=ja
@@ayumishintani7044 Thank you so much!!
I really appreciate it!
Why with the time-varying exposure method (around 10:00) you are still using 1 as the numerator in the non-transplant group? Why wouldn't it be 3?
Yes, I have the same question as you. I think it should be 3
I intend to analyse survival analysis for companies. If I have to run cox regression for the same set of companies for 10 years, is the procedure same in spss. How do I go about. The same set of variables are studied, but the values of these variables change. Kindly help me as I am stuck.
Dear Ayumi,
Thank you for your video.
I have a (naive ?) question regarding the Cox model, particularly about one covariate, measured only at baseline ...
As this covariate is related with the severity of a medical condition, I can assume this covariate can change over the time, but I don't have any follow-up data for it ...
So here is my question : do you think it is relevant to put a baseline value as covariate in the Cox model to predict an event related to this condition ?
Thanks a lot for your answer.
Kind regards
Hi Ayumi, may I ask if it is possible to do a prediction from time varying survival model to a new dataset? if yes, how should we prepare the dataset for prediction? Thanks in advance, any opinion still help (y)
You would construct a dataset with multiple lines per patient as
ID Start Stop exp Event
1 0 3 0 0 (Censored)
1 3 3 1 0 (Censored)
1 6 1 0 1 (Event)
2 0 5 1 1 (Event)
@@ayumishintani7044 hi ayumi, thank you for your time. Is that the construction is for training the model? If that so, I think I already getting to understand how to construct the dataset for training. What I mean was what if we have trained the model and want to use the model to do a prediction for new dataset? Do we have to set the construction of dataset the same as we prepare it for training but without censor/event status? Thank you before, i am curious about if after i modeled the survival analysis, is it possible to predict with new dataset whether a unique ID will reach event or not and when will it happen, just like logistic regression concept of predicting probability but no timing prediction. Pardon me on my grammar 😁
@@randylawrentius9760 Computing predicted probability in Cox regression for validation dataset is much more difficult than that for logistics regression. Logistic regression has an intercept in the model, Cox regression does not. Cox regression instead has baseline hazards which is non-parametric. You need to consider baseline hazard in the prediction in the Cox regression. You can use the baseline hazards from the training dataset, or can update baseline hazard from the validation dataset with beta-coeff from the training dataset. In the later case, you should fit data from the validation dataset with censoring variable and borrow the baseline hazard from the validation dataset analysis while bata-coef from the training dataset-analysis.