1. God p?ske to everyone! ¡­

1. God p?ske to everyone! So there's no teaching Mon 6 or Mon 13 April.

2. For Mon 20 April, we continue our Ch 6 efforts. Work through the following exercises:

A: For the 189 babies & mothers, let as before x1 = 1, x2 = mother's weight (in kg) before pregnancy, z1 = age, z2 = 1(race==2), z3 = 1(race==3), with race being 1 (white), or 2 (black), or 3 (other). Keep x1, x2 protected and z1, z2, z3 open, with 2^3 = 8 submodels. For each focus parameter mu (given in a minute): compute all eight estimates; estimate the mse; compute the FIC score; give a FIC plot (with FIC or estimated mse on x axis and estimates on y axis). For mu, take (i) probability pwhite of low birthweight, for white mother, age 33, weight 55; (ii) same probability pblack, but for black mother; (iii) the ratio pblack/pwhite.

B: For the n = 250 best speedskaters on the Adelskalenderen, with results y1, y2, y3, y4, we study linear regressions of y2 w.r.t. y1, y3, y4, with y1 protected, with a total of four candidate models (0, 3, 4, 34); cf. Nils Exercise 6. For each focus parameter mu of interest: compute the four estimates; estimate mse; compute FIC score; display a FIC plot. For mu, take (i) expected y2, for a skater with 35.00, 6:20.00, 13:35.00; (ii) the probability that ?ystein Gr?dum will skate a 1500-m at 1:48.00 or better (his PBs, as we know, are 39.10, 6:15.50, 12:56.38). Extend your analyses to include the 13plus3 model of Nils Exercise 6.