Hello All,
In a randomized cluster model I want to
estimate heteroscedasticity at the second level by adding the grouping variable
as random parameter and constraining the associated variance component to zero,
leaving the variance associated with the intercept and the covariance to be
estimated (Snijders and Bosker, 1999, p. 119).
I used the following function to get the variance
covariance matrix: <- lme(respons ~ treat + x + z,
data = "" random = ~ treat, cluster = ~ clust)
I get (among other output) the matrix:
(Intercept)
treat
(Intercept)
0.0252191 0.04445075
treat
0.7070917 0.15670289
I have two questions:
1) How can it be accomplished that the value in cell
[2,2] is restricted to zero;
2) How should the value of cell [1,2] be interpreted
and can it been restricted to zero?
Thank you in advance, for your answer.
Kind regards,
Elly Korendijk
Department of Methodology and Statistics
Faculty of Social Sciences
Universiteit Utrecht
Heidelberglaan 2, De Uithof
P.O. Box 80140, 3508 TC Utrecht, The Netherlands
Telephone: +31 30 253 14 90 / 44
38
Fax:
+31 30 253 57 97
E-mail: E.J.H.Korendijk@fss.uu.nl