3. Suppose that we observe two random variables X1, X2, each with a Poisson distribution and mean parameters di and A2 respectively (the pmf for the Poisson distribution in in section 2.4 of the notes, page 23 in backgroundIntro.pdf). For i = 1, 2, let O; = log A¡ = a + Bzi where z1 = 0 and z2 = 1. Suppose that we observe X1 = x1 and X2 = r2 (x; 2 0). (a) Compute the maximum likelihood estimate of a under the null hypothesis Ho: B = 0. (b) Derive the score test for Ho: B = 0. (c) Now let X1+X2 = m and derive the conditional distribution of X2 given m as a function of a and B, a2 and m. (d) Derive the score test for Ho: B = 0 using the conditional distribution. (e) Suppose that in a two-armed randomized trial with equal numbers of subjects per arm we observe 65 and 49 deaths in groups A and B respectively. Assuming that the numbers of deaths follow a Poisson distribution, perform the score test for the null hypothesis that the death rates are the same in the two arms. (Note that this procedure gives a "quick and dirty" uway of assessing the statistical significance of event rates between two equal sized groups.)

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Solve part A, B and C 

 

3. Suppose that we observe two random variables X1, X2, each with a Poisson distribution and
mean parameters di and A2 respectively (the pmf for the Poisson distribution in in section
2.4 of the notes, page 23 in backgroundIntro.pdf). For i = 1,2, let
0; = log A; = a + Bz;
where z1 = 0 and z2 = 1. Suppose that we observe X1 = x1 and X2 = r2 (x; 2 0).
(a) Compute the maximum likelihood estimate of a under the null hypothesis Ho: B = 0.
(b) Derive the score test for Ho: B = 0.
(c) Now let X1+X2 = m and derive the conditional distribution of X2 given m as a function
of a and 3, r2 and m.
(d) Derive the score test for Ho: B = 0 using the conditional distribution.
(e) Suppose that in a two-armed randomized trial with equal numbers of subjects per arm
we observe 65 and 49 deaths in groups A and B respectively. Assuming that the numbers
of deaths follow a Poisson distribution, perform the score test for the null hypothesis
that the death rates are the same in the two arms.
(Note that this procedure gives a “quick and dirty" way of assessing the statistical significance
of event rates between two equal sized groups.)
Transcribed Image Text:3. Suppose that we observe two random variables X1, X2, each with a Poisson distribution and mean parameters di and A2 respectively (the pmf for the Poisson distribution in in section 2.4 of the notes, page 23 in backgroundIntro.pdf). For i = 1,2, let 0; = log A; = a + Bz; where z1 = 0 and z2 = 1. Suppose that we observe X1 = x1 and X2 = r2 (x; 2 0). (a) Compute the maximum likelihood estimate of a under the null hypothesis Ho: B = 0. (b) Derive the score test for Ho: B = 0. (c) Now let X1+X2 = m and derive the conditional distribution of X2 given m as a function of a and 3, r2 and m. (d) Derive the score test for Ho: B = 0 using the conditional distribution. (e) Suppose that in a two-armed randomized trial with equal numbers of subjects per arm we observe 65 and 49 deaths in groups A and B respectively. Assuming that the numbers of deaths follow a Poisson distribution, perform the score test for the null hypothesis that the death rates are the same in the two arms. (Note that this procedure gives a “quick and dirty" way of assessing the statistical significance of event rates between two equal sized groups.)
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