On 27-Feb-10 17:57:56, Cardinals_Fan wrote:
>
> One last question. I'm trying to use the rnorm() function to
> draw a distribution for my coefficient estimates. Let's say
> I have a model y* = a + b1x1. I have the coefficient estimate
> for b1 stored as b1 and the standard error estimate for b1
On 2010-02-27 10:57, Cardinals_Fan wrote:
One last question. I'm trying to use the rnorm() function to draw a
distribution for my coefficient estimates. Let's say I have a model y* = a
+ b1x1. I have the coefficient estimate for b1 stored as b1 and the
standard error estimate for b1 stored as
One last question. I'm trying to use the rnorm() function to draw a
distribution for my coefficient estimates. Let's say I have a model y* = a
+ b1x1. I have the coefficient estimate for b1 stored as b1 and the
standard error estimate for b1 stored as s1. I run rnorm function as
a <- rnorm(10
On 2010-02-27 1:38, (Ted Harding) wrote:
On 27-Feb-10 03:52:19, Cardinals_Fan wrote:
Hi, I am a stata user trying to transition to R. Typically I
compute marginal effects plots for (example) probit models by
drawing simulated betas by using the coefficient/standard error
estimates after I ru
On 27-Feb-10 03:52:19, Cardinals_Fan wrote:
>
> Hi, I am a stata user trying to transition to R. Typically I
> compute marginal effects plots for (example) probit models by
> drawing simulated betas by using the coefficient/standard error
> estimates after I run a probit model. I then use these
Hi, I am a stata user trying to transition to R. Typically I compute
marginal effects plots for (example) probit models by drawing simulated
betas by using the coefficient/standard error estimates after I run a probit
model. I then use these simulated betas to compute first difference
marginal
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