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Back to the forum  2018-06-22 19:27 CEST (UTC+2h)

confint() for difference of effect levels [R for BE/BA]

posted by ElMaestro - Denmark, 2017-08-29 14:45  - Posting: # 17751
Views: 2,338

(edited by ElMaestro on 2017-08-29 14:58)

Hi d_labes,

thanks for your input.

» No. confint() gives you confidence intervals for the model parameters only.

Except when we fit the model with intercept, treatment first. Now the SE for whichever treatment is not the intercept, is the SE of the difference (and the other treatment effect is unestimable because of the intercept). The funny logic of linear models. I need to get my head around that aspect.

» Or if you prefer using such beasts like "least square means" have a look at package lsmeans.

When we look at treatment effect differences it does not matter how we define the effects by contrast coding. I don't absolutely need an LSMean; I can do with two model effects calcuated in any valid way as long as I can extract their difference.

» BTW: All-at-once is not the preferred method of a big regulatory body.

Yes, I have heard of that big regulatory body. But there is a problem. All-at-once is the preferred method of another big regulatory body.:-D:-D:-D:-D

» Pairwise lm objects (throwing away the data under those treatments not under consideration) will give you the opportunity to use confint() to derive CI's.
So if we are not considering the big agency, but the other big agency :-), and we are not throwing away treatments when fitting models, how would you approach the CI derivation in R?

Many thanks.

if (3) 4

Best regards,

"(...) targeted cancer therapies will benefit fewer than 2 percent of the cancer patients they’re aimed at. That reality is often lost on consumers, who are being fed a steady diet of winning anecdotes about miracle cures." New York Times (ed.), June 9, 2018.

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