PROC GAMPL is used to model a non-linear relationship between patient age and hospital readmission. Which aspect of PROC GAMPL's penalized spline distinguishes it from including polynomial terms in PROC LOGISTIC?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because PROC GAMPL's penalized splines use a data-driven smoothing parameter (via restricted maximum likelihood or similar criterion) that automatically balances flexibility and smoothness. Polynomial regression requires the analyst to pre-specify degree (linear, quadratic, cubic), which can be under- or over-specified.
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Full Explanation
B is correct because PROC GAMPL's penalized splines use a data-driven smoothing parameter (via restricted maximum likelihood or similar criterion) that automatically balances flexibility and smoothness. Polynomial regression requires the analyst to pre-specify degree (linear, quadratic, cubic), which can be under- or over-specified. A is wrong; PROC GAMPL splines are not constrained to monotonicity. C is wrong; PROC GAMPL works for various distributions including binary. D is wrong; standardization is not required by PROC GAMPL.