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2 parents eb015c8 + 236de11 commit 6c8e490Copy full SHA for 6c8e490
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src/stan-users-guide/regression.qmd
@@ -529,7 +529,7 @@ effect $\beta_k$ for age group $k$ to make a linear predictor $\alpha +
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subtract from each $\beta_k$ and get exactly the same likelihood.
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The traditional approach to identifying such a model is to pin the
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-first varing effect to zero, i.e., $\beta_1 = 0$. With one of the
+first varying effect to zero, i.e., $\beta_1 = 0$. With one of the
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varying effects fixed, you can no longer add a constant to all of them
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and the model's likelihood is identified. In addition to the
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difficulty in specifying such a model in Stan, it is awkward to
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