A review of Stata 8.1 and its time series by Christopher F. Baum PDF

By Christopher F. Baum

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Here Q = (Q,, . . , Q,)' is the vector of adjusted treatment totals Qi as defined for a BIB design and the solution matrix M = { m,} is given by m.. 22) otherwise where For this design all contrasts c'8 are estimable, and cov(c$, C;6)= u 2 c ~ M c 2 V e l ,cz E Ck where C" = { c E Rk :C:=, ci = 0) is the k-dimensional contrast space. We can thus take V = M . We then have var(ii - 3) = 2p (az2+ 6,,)(r2 if i and j are first associates if i and j are second associates . 9) of Chapter 3) unless A, = A,, in which case the design reduces to a BIB design.

As noted before, N( y, aZLVL‘). The LR test of H,: y = yo versus H,:y f yo, where yo = (yol,yo*,. . , yo,,,)’ is a specified vector, is of the form +- where we have assumed that L is a full row rank matrix. 10) 5 is a critical constant to be chosen so as to make the level of the test equal to a. f. and hence 6 = FZ,),,, the upper a point of that distribution. 10). 4 Examples (One-way Layout). Consider a single qualitative factor with k 2 2 levels (treatments). 1 K,=6’,+ E,, (lSiSk,lSjSn,). 12) In this case the unique LS estimates of the 6,’s are given by = Y,= ( l S i d k).

In the exploratory phase of research it is common to start with a large number of chemicals with structures related to a known active compound (Dunnett and Goldsmith 1981). Therefore a screening device is needed to weed out potential noncontenders. An MCP can be used for this purpose. ) The choice of error rate and associated a depends on the costs of confirmation, relative costs of Type I versus Type I1 errors, and prior experiences with similar problems. One choice that is reasonable in some situations is the Type I PFE whose control guarantees a bound on the expected number of false leads.

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A review of Stata 8.1 and its time series by Christopher F. Baum


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