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RE: st: growth curve model with weights

From   P C <>
Subject   RE: st: growth curve model with weights
Date   Thu, 18 Jun 2009 07:08:35 -0700 (PDT)

Thanks to Stas for giving me the coding examples. Also to Nick for explaining the word for "equidistant in time". 

The sample I will be working on has a large sample size. It has over 15,000 cases. Will it take long for gllamm to estimate the growth curve model. 

Just to double check: 

When I specify student-level weight like gen wt2 = [student level weight], suppose I have three waves (w1weight; w2weight; w3weight), when I list them in a hierarachical order in the data file, the [student level weight] is no more a constant but changes within each respondent, right?

The other thing is that when I specify school-level weight, gen wt3 = [school level weight], I should use the method suggested in Sophia's paper to construct the school-level weight, right?



--- On Wed, 6/17/09, Nick Cox <> wrote:

> From: Nick Cox <>
> Subject: RE: st: growth curve model with weights
> To:
> Date: Wednesday, June 17, 2009, 1:34 PM
> "regular" carries the precise sense
> of equally spaced. 
> It also sometimes carries an informal sense of frequent,
> regardless of
> spacing. 
> Stas asked: equidistant in time ... is there a proper long
> English word
> for that?
> Nick 
> Stas Kolenikov
> Look up chapter 3 of GLLAMM manual. Section 3.2 describes
> the general
> framework for two-level random coefficient model, of which
> the growth
> model is a special case. You will have two latent factors
> at student
> level, one will be loading on the vector of 1's (the
> intercept), and
> the other one on time (the growth rate; the wave number in
> the simple
> case if they are equidistant in time... NJC, is there a
> proper long
> English word for that?). 
> [...] 
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