1975
DOI: 10.1007/bf02291765
|View full text |Cite
|
Sign up to set email alerts
|

Probability spaces, hilbert spaces, and the axioms of test theory

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
104
0
1

Year Published

1999
1999
2020
2020

Publication Types

Select...
7
2

Relationship

0
9

Authors

Journals

citations
Cited by 104 publications
(105 citation statements)
references
References 2 publications
0
104
0
1
Order By: Relevance
“…The paper is organized as follows: In the next section, a brief overview of the CFA approach to MTMM data and its problems is given. Then, a new model is introduced that was developed in the tradition of Zimmerman's (1975Zimmerman's ( , 1976) and Steyer's (1989) work on classical psychometric test theory (CTT). It is shown that the trait and method factors can be defined as functions of the true-score variables.…”
Section: Introductionmentioning
confidence: 99%
“…The paper is organized as follows: In the next section, a brief overview of the CFA approach to MTMM data and its problems is given. Then, a new model is introduced that was developed in the tradition of Zimmerman's (1975Zimmerman's ( , 1976) and Steyer's (1989) work on classical psychometric test theory (CTT). It is shown that the trait and method factors can be defined as functions of the true-score variables.…”
Section: Introductionmentioning
confidence: 99%
“…With the expected value definition of true score in (5), the parallelism of the forms and the assumption of linear experimental independence lbr different measurements, the CTT model can be obtained by "construction" rather than assumption (see Lord and Novick, 1968;Zimmerman, 1975Zimmerman, , 1976 to give:…”
Section: Es) = 0 (8)mentioning
confidence: 99%
“…They may have possibly different variances, say ψ 11 , ψ 22 , · · · , ψ pp . Thus, τ and the components of X and e are all regarded as random variables for a populations of examinees (Zimmerman, 1975). The p-component vector µ is treated as the mean score vector of X.…”
Section: Introductionmentioning
confidence: 99%