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hbiostat.org | ||
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www.rdatagen.net
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| | | | | I was thinking a lot about proportional-odds cumulative logit models last fall while designing a study to evaluate an intervention's effect on meat consumption. After a fairly extensive pilot study, we had determined that participants can have quite a difficult time recalling precise quantities of meat consumption, so we were forced to move to a categorical response. (This was somewhat unfortunate, because we would not have continuous or even count outcomes, and as a result, might not be able to pick up small changes in behavior.) We opted for a question that was based on 30-day meat consumption: none, 1-3 times per month, 1 time per week, etc. - six groups in total. The question was how best to evaluate effectiveness of the intervention? | |
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fharrell.com
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| | | | | This article shows an example formally testing for heterogeneity of treatment effect in the GUSTO-I trial, shows how to use penalized estimation to obtain patient-specific efficacy, and studies variation across patients in three measures of treatment effect. | |
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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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www.randomservices.org
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| | | [AI summary] The text covers various topics in probability and statistics, including continuous distributions, empirical density functions, and data analysis. It discusses the uniform distribution, rejection sampling, and the construction of continuous distributions without probability density functions. The text also includes data analysis exercises involving empirical density functions for body weight, body length, and gender-specific body weight. | ||
