that's a great question, Mike.
So here's the deal: Usually, the expected values will differ across
columns only because the X observations are different. In this case, the
X observations are all the same (intercept = 1 and treat = 1, for
example), so each column looks the same. The ev differ across rows
because of the differences in the simulated betas.
The predicted values are draws from the distribution defined by the
corresponding value in the expected value matrix (and so should be
different across rows and columns).
----- Original Message -----
From: "Michael Richard Kellermann" <kellerm(a)fas.harvard.edu>
To: <gov2001-l(a)lists.fas.harvard.edu>
Sent: Thursday, December 09, 2004 11:05 AM
Subject: Re: [gov2001-l] setx question
Here is the reason for my question: when I look at the expected values
generated by the sim command, using a normal model, they are the same in
the univariate case:
s.out.0$qi$ev[1:8, 1:8]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
[1,] 0.4486 0.4486 0.4486 0.4486 0.4486 0.4486 0.4486 0.4486
[2,] 0.4424 0.4424 0.4424 0.4424 0.4424 0.4424 0.4424 0.4424
[3,] 0.4392 0.4392 0.4392 0.4392 0.4392 0.4392 0.4392 0.4392
[4,] 0.4425 0.4425 0.4425 0.4425 0.4425 0.4425 0.4425 0.4425
[5,] 0.4411 0.4411 0.4411 0.4411 0.4411 0.4411 0.4411 0.4411
[6,] 0.4485 0.4485 0.4485 0.4485 0.4485 0.4485 0.4485 0.4485
[7,] 0.4477 0.4477 0.4477 0.4477 0.4477 0.4477 0.4477 0.4477
[8,] 0.4485 0.4485 0.4485 0.4485 0.4485 0.4485 0.4485 0.4485
and then they are different for the predicted values:
s.out.0$qi$pr[1:8, 1:8]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
[1,] 0.26540 0.69574 -0.30079 0.7086 0.095671 0.56353 0.5045 0.7559
[2,] -0.29949 0.79896 1.81914 -0.2224 0.149480 0.07857 0.9538 -0.7112
[3,] -0.24355 0.54188 0.47502 1.1169 0.675997 0.88817 0.1099 -0.1553
[4,] -0.02701 -0.28023 0.75768 -0.2701 0.296251 0.86762 0.3645 0.5838
[5,] 0.27580 0.46741 0.36535 0.4150 1.234477 0.40665 0.5650 0.9518
[6,] 0.33215 0.81140 0.39242 0.7009 0.282338 0.97523 0.7354 0.1146
[7,] -0.29423 0.09349 0.01257 1.0007 0.721501 0.12567 0.3155 0.0861
[8,] 0.24989 0.28098 1.38814 0.6617 -0.007151 -0.19204 0.6433 0.5431
So I guess my question more precisely is, does sim take one set of draws
from the sampling distribution of the betas and reuse it for all of the
sets of starting values?
Also, for the normal model, should we be using the predicted values or
the
expected values to calculate the ATE and ATT?
Cheers,
Mike
On Thu, 9 Dec 2004, Olivia Lau wrote:
There's nothing random about setx(). The
randomness comes in sim().
And my
understanding of how R handles seeds is that it picks up where it left
off.
Hence,
a <- rnorm(10)
b <- rnorm(10)
identical(a, b)
should be false...
----- Original Message -----
From: "Michael Richard Kellermann" <kellerm(a)fas.harvard.edu>
To: <gov2001-l(a)lists.fas.harvard.edu>
Sent: Thursday, December 09, 2004 10:39 AM
Subject: Re: [gov2001-l] setx question
Does Zelig start with the same random number seed for each vector of x
values created by the setx command?
Cheers,
Mike
On Thu, 9 Dec 2004, Olivia Lau wrote:
> If you can't get Zelig to do what you want (right now, before section
> this
> evening), I suggest that you manhandle the output to get it to
> produce
> what
> you want...just a thought.
>
> ----- Original Message -----
> From: "Andrew Eggers" <aeggers(a)gmail.com>
> To: <gov2001-l(a)lists.fas.harvard.edu>
> Sent: Thursday, December 09, 2004 10:23 AM
> Subject: [gov2001-l] setx question
>
>
> > Can anyone help me understand why my setx function isn't doing what
> > I
> > thought it would?
> >
> > I'm doing part 2a.
> >
> >> x.out0<- setx(z.out, fn= NULL, phone =0)
> >
> >> x.out0[1:10,]
> > (Intercept) phone
> > 1 1 1
> > 2 1 0
> > 3 1 1
> > 4 1 0
> > 5 1 1
> > 6 1 1
> > 7 1 1
> > 8 1 1
> > 9 1 1
> > 10 1 1
> >
> > I thought this would produce all 0's in the phone column of x.out0,
> > but clearly it didn't.
> >
> > Thank you!
> >
> > Andy
> > _______________________________________________
> > gov2001-l mailing list
> > gov2001-l(a)lists.fas.harvard.edu
> >
http://lists.fas.harvard.edu/mailman/listinfo/gov2001-l
> >
>
> _______________________________________________
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>
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>
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