/explore
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hbiostat.org | ||
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kgoldfeld.github.io
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| | | | | Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR). | |
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www.robertkubinec.com
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| | | | | Ordered beta regression can give you comparable, scale-free ATEs that can still be understood in the scale of the original data-all without using logs. | |
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fharrell.com
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| | | | | Many researchers worry about violations of the proportional hazards assumption when comparing treatments in a randomized study. Besides the fact that this frequently makes them turn to a much worse approach, the harm done by violations of the proportional odds assumption usually do not prevent the proportional odds model from providing a reasonable treatment effect assessment. | |
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jaketae.github.io
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| | | In this post, we will continue our journey down the R road to take a deeper dive into data frames. R is great for data analysis and wranging when it comes to dealing with tabular data, especially thanks to the dplyr package, which is R's equivalent of Python's pandas. | ||
