Timeline for What kind of model is best suited for this type of data and research question?
Current License: CC BY-SA 4.0
7 events
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| Apr 28, 2023 at 8:06 | comment | added | EulersNumber | @EdM Thank you for the response. I indeed have cumulative time-varying covariates, which represent cumulative research output, e.g., cumulative citations up to time t, the cumulative number of publications in top journals up to time t, etc. Most of my covariates are in fact cumulative in nature, which was not clear from my mock data. Given this, I suppose I am set to proceed with a discrete-time binomial survival model. | |
| Apr 27, 2023 at 20:14 | comment | added | PesKchan | @EdM I Have arrived to bug you again with my new question stats.stackexchange.com/questions/614329/… | |
| Apr 27, 2023 at 19:21 | comment | added | EdM | @EulersNumber the advantage of treating this like a survival model is that you naturally take into account things like time since receiving a doctoral degree (if that's the type of researcher in question). The problem with either a binomial or a survival model is that they evaluate covariate values in place at the event time. Academic promotions or prizes depend on cumulative achievement. So you need some cumulative measure of "output" instead of year-by-year, however you choose to set up the model. With that caution, a discrete-time binomial survival model seems like a good choice. | |
| Apr 27, 2023 at 16:34 | comment | added | EulersNumber | Regarding your warning, I do not believe that the occurence of the event would greatly affect the independent variables in the same time period, because the event is not that significant. Moreover, the link is clearly stronger and quite obvious in the other direction. However, I will consider this more carefully for sure. Given all of these clarifications, would your suggestions change in any way? You can ask me for more details if needed. | |
| Apr 27, 2023 at 16:28 | comment | added | EulersNumber | Thanks for the thorough answer. It seems that you correctly understood the essence of the data. Nevertheless, here are some clarifications that may or may not affect your suggestions: 1) Data is about researchers, where most time-varying independent variables are measures of research output / accomplishments 2) Event is sort of a promotion or a prize. Most of all I want to understand what variables explain receiving that promotion / prize. Not so much the time between a reference date (say e.g., PhD completion year) and the event - albeit this could be the reference date if one is needed | |
| Apr 27, 2023 at 15:30 | history | edited | EdM | CC BY-SA 4.0 |
Added warning about causal direction of predictors/event
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| Apr 27, 2023 at 14:46 | history | answered | EdM | CC BY-SA 4.0 |