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I am reading some lecture notes on Factorial Experiments.

Remark 6.1 In this course we only treat the linear model. The response variable may however be a (Poisson) count, or a (Binomial) number of successes or generally an outcome for which another distribution than the normal seems appropriate. Many considerations about factorial experimentation can be applied to the generalised linear model as introduced in STATG001, too. Computations can no longer be carried out manually but R’s glm-function will do what is required in order to estimate and test effect.

So effects in linear model can from the coefficient of the relevant regression matrices. (or we can just calculated by hand if our experiment has just $2^3$ factors.)

For a GLM, do I just set up the design matrix like in linear regression and select the appropriate model? Do exactly the same thing as before?

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For a GLM, do I just set up the design matrix like in linear regression and select the appropriate model? Do exactly the same thing as before?

Yes, the design matrix will be the same. You will need to specify the relevant distribution (eg binomial) and possibly a link function (eg logit for logistic regression and log for poisson)

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  • $\begingroup$ @Lost1 does this answer your question ? If so please consider marking it as the accepted answer. If not, please let me know why. $\endgroup$ Jan 21, 2020 at 12:04

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