From: Rense Nieuwenhuis <r.nieuwenhuis_at_student.ru.nl>

Date: Sun, 10 Jun 2007 16:35:58 +0200

R-help_at_stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Sun 10 Jun 2007 - 15:04:48 GMT

Date: Sun, 10 Jun 2007 16:35:58 +0200

library(nlme)

library(mlmRev)

lme(fixed = normexam ~ standLRT,

data = Exam, random = ~ 1 | school)

If I want to model only a few categories of variance, all works fine. For instance, should I (for whatever reason) hypothesize that the variance on the normexam-scores is larger in mixed schools than in boys-schools, I'd use weights = varIdent(form = ~ 1 | type), leading to:

heteroscedastic <- lme(fixed = normexam ~ standLRT,

data = Exam, weights = varIdent(form = ~ 1 | type), random = ~ 1 | school)

This gives me nice and clear output, part of which is shown below:
Variance function:

Structure: Different standard deviations per stratum
Formula: ~normexam | type

Parameter estimates:

Mxd Sngl

1.000000 1.034607

Number of Observations: 4059

Number of Groups: 65

Though, should I hypothesize that the variance on the normexam-
variable is larger on schools that have a higher average score on
intake-exams (schavg), I run into troubles. I'd use weights = varIdent

(form = ~ 1 | schavg), leading to:

heteroscedastic <- lme(fixed = normexam ~ standLRT,

data = Exam, weights = varIdent(form = ~ 1 | schavg), random = ~ 1 | school)

This leads to estimation problems. R tells me: Error in lme.formula(fixed = normexam ~ standLRT, data = Exam, weights = varIdent(form = ~1 | :

nlminb problem, convergence error code = 1; message = iteration limit reached without convergence (9)

Fiddling with maxiter and setting an unreasonable tolerance doesn't help. I think the origin of this problem lies within the large number of categories on "schavg" (65), that may make estimation troublesome.

This leads to my two questions:

- How to solve this estimation-problem?

- Is is possible that the varIdent (or more general: VarFunc) of lme
returns a single value, representing a coëfficiënt along which
variance is increasing / decreasing?

- In general: how can a variance-component / heteroscedasticity be made dependent on some level-2 variable (school level in my examples) ?

Many thanks in advance,

Rense Nieuwenhuis

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Sun 10 Jun 2007 - 15:04:48 GMT

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