Question: Use the fitted model from the previous exercise to compute the linear trend coefficient [ frac{sum tleft(hat{gamma}_{1}(t)-hat{gamma}_{0}(t)ight)}{sum t^{2}} ] and its standard error. You should

Use the fitted model from the previous exercise to compute the linear trend coefficient
\[
\frac{\sum t\left(\hat{\gamma}_{1}(t)-\hat{\gamma}_{0}(t)ight)}{\sum t^{2}}
\]
and its standard error. You should find both numbers in the range \(0.013-0.015\) per month, similar to, but not exactly the same as those reported in the text.


Data From previous exercise 

According to the text in Sect. 5.5, Virtual randomization requires the timezero average for feral hosts to be the same as that for giant runts, but the temporal trends are otherwise unconstrained. It appears that the model matrix spanning this subspace is not constructible using factorial model formulae. Explain how to construct the desired matrix including a constant additive sex effect. What is its rank? Fit the model as described in the text following Table 5.4. Include independent Brownian motions for aviaries and lineages, plus an additional baseline error term with independent and identically distributed components.

0 Diff 0.000 s.e. 0.00 Ratio 0.00 Time in months 24 6

0 Diff 0.000 s.e. 0.00 Ratio 0.00 Time in months 24 6 12 18 -0.114 0.111 0.464 0.24 0.33 0.40 -0.48 0.34 1.16 30 36 42 48 0.496 0.316 0.251 0.494 0.750 0.46 0.51 0.56 0.60 0.65 1.09 0.62 0.45 0.82 1.16

Step by Step Solution

3.32 Rating (158 Votes )

There are 3 Steps involved in it

1 Expert Approved Answer
Step: 1 Unlock

To compute the linear trend coefficient and its standard error using the provided formula and data we first need to understand what each symbol repres... View full answer

blur-text-image
Question Has Been Solved by an Expert!

Get step-by-step solutions from verified subject matter experts

Step: 2 Unlock
Step: 3 Unlock

Students Have Also Explored These Related Applied Statistics And Probability For Engineers Questions!