Displaying 5 results from an estimated 5 matches for "normexam".
2007 Jun 10
1
{nlme} Multilevel estimation heteroscedasticity
Dear All,
I'm trying to model heteroscedasticity using a multilevel model. To
do so, I make use of the nlme package and the weigths-parameter.
Let's say that I hypothesize that the exam score of students
(normexam) is influenced by their score on a standardized LR test
(standLRT). Students are of course nested in "schools". These
variables are contained in the Exam-data in the mlmRev package.
library(nlme)
library(mlmRev)
lme(fixed = normexam ~ standLRT,
data = Exam,
random = ~ 1 | school)...
2005 Jul 12
2
testing for significance in random-effect factors using lmer
Hi, I would like to know whether it is possible to obtain a value of
significance for random effects when aplying the lme or related
functions. The default output in R is just a variance and standard
deviation measurement.
I feel it would be possible to obtain the significance of these random
effects by comparing models with and without these effects. However,
I'm not used to perform
2007 Jul 30
1
Extract random part of summary nlme
...Exam
AIC BIC logLik
9158.56 9234.241 -4567.28
Random effects:
Formula: ~type | school
Structure: General positive-definite, Log-Cholesky parametrization
StdDev Corr
(Intercept) 0.2869401 (Intr)
typeSngl 0.2791040 -0.617
Residual 0.7302233
Fixed effects: normexam ~ sex + standLRT + vr + intake + type
Value Std.Error DF t-value p-value
(Intercept) 0.2326861 0.09350662 3990 2.488445 0.0129
sexM -0.1533822 0.03169762 3990 -4.838921 0.0000
standLRT 0.3859356 0.01677195 3990 23.010776 0.0000
vrmid 50% 0.076...
2007 Jul 31
1
Extracting random parameters from summary lme and lmer
...Exam
AIC BIC logLik
9158.56 9234.241 -4567.28
Random effects:
Formula: ~type | school
Structure: General positive-definite, Log-Cholesky parametrization
StdDev Corr
(Intercept) 0.2869401 (Intr)
typeSngl 0.2791040 -0.617
Residual 0.7302233
Fixed effects: normexam ~ sex + standLRT + vr + intake + type
Value Std.Error DF t-value p-value
(Intercept) 0.2326861 0.09350662 3990 2.488445 0.0129
sexM -0.1533822 0.03169762 3990 -4.838921 0.0000
standLRT 0.3859356 0.01677195 3990 23.010776 0.0000
vrmid 50% 0.076...
2007 Jul 30
0
Extracting random parameters from summary lme
...Exam
AIC BIC logLik
9158.56 9234.241 -4567.28
Random effects:
Formula: ~type | school
Structure: General positive-definite, Log-Cholesky parametrization
StdDev Corr
(Intercept) 0.2869401 (Intr)
typeSngl 0.2791040 -0.617
Residual 0.7302233
Fixed effects: normexam ~ sex + standLRT + vr + intake + type
Value Std.Error DF t-value p-value
(Intercept) 0.2326861 0.09350662 3990 2.488445 0.0129
sexM -0.1533822 0.03169762 3990 -4.838921 0.0000
standLRT 0.3859356 0.01677195 3990 23.010776 0.0000
vrmid 50% 0.076...