Description Usage Arguments Value Methods (by class) References Examples
gstudy
estimates variance components attributable to objects of measurement (e.g., persons) and facets (e.g., items and raters), as well as unexplained variation.
1 2 3 4 5 6 7 8 9 10 11 12 13  gstudy(data, ...)
## S3 method for class 'data.frame'
gstudy(data, formula, colname.strata = NULL,
colname.objects = NULL, keep.mer = F, ...)
## S3 method for class 'univariate'
gstudy(data, formula, colname.strata = NULL,
colname.objects = NULL, keep.mer = F, ...)
## S3 method for class 'multivariate'
gstudy(data, formula, colname.strata = NULL,
colname.objects = NULL, keep.mer = F, ...)

data 
a data frame in long format with a column for item scores and columns for sources of variance 
... 
additional arguments to be passed to 
formula 
a formula specifying the model to be estimated by 
colname.strata 
an optional string that specifies the name of the column containing strata (if conducting a multivariate G study) 
colname.objects 
an optional string that specifies the name of the column containing objects of measurement for calculating observedscore covariance (if conducting a multivariate G study) 
keep.mer 
a logical indicating whether or not to store the output from 
an object of class "gstudy
" that lists variance components of class "components
". It will also list observedscore variance and covariance between strata if you specify the names of the columns identifying strata and objects of measurement.
data.frame
: G study of a data.frame
object
univariate
: G study of a univariate
object
multivariate
: G study of a multivariate
object
Brennan, R. L. (2001). Generalizability theory. New York: Springer.
Rajaratnam, N., Cronbach, L. J., & Gleser, G. C. (1965). Generalizability of stratifiedparallel tests. Psychometrika, 30(1), 3956.
1 2 3 4 5 6 7 8 9 10 11 12 13  #Conduct a univariate G study.
#Compare to results on page 116 of Brennan (2001).
data(Brennan.3.2)
formula.Brennan.3.2 < "Score ~ (1  Person) + (1  Task) +
(1  Rater:Task) + (1  Person:Task)"
gstudy(data = Brennan.3.2, formula = formula.Brennan.3.2)
#Conduct a multivariate G study.
#Compare to results on page 270 of Brennan (2001).
data(Rajaratnam.2)
formula.Rajaratnam.2 < "Score ~ (1  Person) + (1  Item)"
gstudy(data = Rajaratnam.2, formula = formula.Rajaratnam.2, colname.strata = "Subtest",
colname.objects = "Person")

Loading required package: lme4
Loading required package: Matrix
$components
source var percent n
1 Person:Task 0.5595679 12.8 1
2 Rater:Task 0.6475309 14.8 1
3 Person 0.4731482 10.8 1
4 Task 0.3251542 7.4 1
5 Residual 2.3802469 54.3 1
attr(,"class")
[1] "gstudy" "list"
$within
$within$`1`
$within$`1`$components
source var percent n
1 Person 1.5714285 61.1 1
2 Item 0.4285715 16.7 1
3 Residual 0.5714286 22.2 1
$within$`2`
$within$`2`$components
source var percent n
1 Person 2.7857142 68.7 1
2 Item 0.1994048 4.9 1
3 Residual 1.0714286 26.4 1
$within$`3`
$within$`3`$components
source var percent n
1 Person 1.8571429 68.0 1
2 Item 0.4464286 16.3 1
3 Residual 0.4285714 15.7 1
$between
$between$var.obs
1 2 3
1 1.857143 1.4821429 0.5000000
2 1.482143 3.0535714 0.9464286
3 0.500000 0.9464286 2.0714286
attr(,"colname.objects")
[1] "Person"
attr(,"class")
[1] "gstudy" "list"
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