Results 1 
9 of
9
The Theoretical Status of Latent Variables
 Psychological Review
, 2003
"... This article examines the theoretical status of latent variables as used in modern test theory models. First, it is argued that a consistent interpretation of such models requires a realist ontology for latent variables. Second, the relation between latent variables and their indicators is discussed ..."
Abstract

Cited by 28 (3 self)
 Add to MetaCart
This article examines the theoretical status of latent variables as used in modern test theory models. First, it is argued that a consistent interpretation of such models requires a realist ontology for latent variables. Second, the relation between latent variables and their indicators is discussed. It is maintained that this relation can be interpreted as a causal one but that in measurement models for interindividual differences the relation does not apply to the level of the individual person. To substantiate intraindividual causal conclusions, one must explicitly represent individual level processes in the measurement model. Several research strategies that may be useful in this respect are discussed, and a typology of constructs is proposed on the basis of this analysis. The need to link individual processes to latent variable models for interindividual differences is emphasized. Consider the following sentence: “Einstein would not have been able to come up with his e � mc 2 had he not possessed such an extraordinary intelligence. ” What does this sentence express? It relates observable behavior (Einstein’s writing e � mc 2)toan unobservable attribute (his extraordinary intelligence), and it does so by assigning to the unobservable attribute a causal role in
Conditional Association, Essential Independence and Monotone Unidimensional Item Response Models
 Annals of Statistics
, 1993
"... We consider two recent approaches to characterizing the manifest probabilities of a strictly unidimensional latent variable representation (one satisfying local independence and response curve monotonicity with respect to a unidimensional latent variable) for binary response variables, such as those ..."
Abstract

Cited by 14 (8 self)
 Add to MetaCart
We consider two recent approaches to characterizing the manifest probabilities of a strictly unidimensional latent variable representation (one satisfying local independence and response curve monotonicity with respect to a unidimensional latent variable) for binary response variables, such as those arising from the dichotomous scoring of items on standardized achievement and aptitude tests. Holland and Rosenbaum (1986) show that conditional association is a necessary condition for strict unidimensionality; and Stout (1990) treats the class of essentially unidimensional models, in which the latent variable may be consistently estimated as the length of the response sequence grows using the proportion of positive responses. Of particular concern are strictly unidimensional representations that are minimally useful in the sense that (1) the latent variable can be consistently estimated from the responses; (2) the regression of proportion of positive responses on the latent variable is mo...
On Reichenbach's common cause principle and Reichenbach's notion of common cause
"... It is shown that, given any finite set of pairs of random events in a Boolean algebra which are correlated with respect to a fixed probability measure on the algebra, the algebra can be extended in such a way that the extension contains events that can be regarded as common causes of the correlation ..."
Abstract

Cited by 12 (5 self)
 Add to MetaCart
It is shown that, given any finite set of pairs of random events in a Boolean algebra which are correlated with respect to a fixed probability measure on the algebra, the algebra can be extended in such a way that the extension contains events that can be regarded as common causes of the correlations in the sense of Reichenbach's definition of common cause. It is shown, further, that, given any quantum probability space and any set of commuting events in it which are correlated with respect to a fixed quantum state, the quantum probability space can be extended in such a way that the extension contains common causes of all the selected correlations, where common cause is again taken in the sense of Reichenbach's definition. It is argued that these results very strongly restrict the possible ways of disproving Reichenbach's Common Cause Principle.
TailMeasurability In Monotone Latent Variable Models
, 1996
"... We consider latent variable models for an infinite sequence (or universe) of manifest (observable) variables that may be discrete, continuous or some combination of these. The main theorem is a general characterization by empirical conditions of when it is possible to construct latent variable model ..."
Abstract

Cited by 11 (3 self)
 Add to MetaCart
We consider latent variable models for an infinite sequence (or universe) of manifest (observable) variables that may be discrete, continuous or some combination of these. The main theorem is a general characterization by empirical conditions of when it is possible to construct latent variable models that satisfy unidimensionality, monotonicity, conditional independence, and tailmeasurability. Tailmeasurability means that the latent variable can be estimated consistently from the sequence of manifest variables even though an arbitrary finite subsequence has been removed. The characterizing, necessary and sufficient, conditions that the manifest variables must satisfy for these models are conditional association and vanishing conditional dependence (as one conditions upon successively more other manifest variables). Our main theorem considerably generalizes and sharpens earlier results of Ellis and Van den Wollenberg (1993), Holland and Rosenbaum (1986), and Junker (1993). It is also ...
Generalized measurement models
, 2004
"... Given a set of random variables, it is often the case that their associations can be explained by hidden common causes. We present a set of welldefined assumptions and a provably correct algorithm that allow us to identify some of such hidden common causes. The assumptions are fairly general and so ..."
Abstract

Cited by 7 (4 self)
 Add to MetaCart
Given a set of random variables, it is often the case that their associations can be explained by hidden common causes. We present a set of welldefined assumptions and a provably correct algorithm that allow us to identify some of such hidden common causes. The assumptions are fairly general and sometimes weaker than those used in practice by, for instance, econometricians, psychometricians, social scientists and in many other fields where latent variable models are important and tools such as factor analysis are applicable. The goal is automated knowledge discovery: identifying latent variables that can be used across diferent applications and causal models and throw new insights over a data generating process. Our approach is evaluated throught simulations and three realworld cases.
Nonparametric item response theory in action: An overview of the Special Issue
 Applied Psychological Measurement
, 2001
"... Although most item response theory (IRT) applications and related methodologies involve model fitting within a single parametric IRT (PIRT) family [e.g., the Rasch (1960) model or the threeparameter logistic model ( 3PLM; Lord, 1980)], nonparametric IRT (NIRT) research has been growing in recent yea ..."
Abstract

Cited by 5 (1 self)
 Add to MetaCart
Although most item response theory (IRT) applications and related methodologies involve model fitting within a single parametric IRT (PIRT) family [e.g., the Rasch (1960) model or the threeparameter logistic model ( 3PLM; Lord, 1980)], nonparametric IRT (NIRT) research has been growing in recent years. Three broad motivations for the development and continued interest in NIRT can be identified: 1. To identify a commonality among PIRT and IRTlike models, model features [e.g., local independence (LI), monotonicity of item response functions (IRFs), unidimensionality of the latent variable] should be characterized, and it should be discovered what happens when models satisfy only weakened versions of these features. Characterizing successful and unsuccessful inferences under these broad model features can be attempted in order to understand how IRT models aggregate information from data. All this can be done with NIRT. 2. Any model applied to data is likely to be incorrect. When a family of PIRT models has been shown (or is suspected) to fit poorly, a more flexible family of NIRT models often is desired. These NIRT models have been used to: (1) assess violations of LI due to nuisance traits (e.g., latent variable multidimensionality) or the testing context influencing test performance (e.g.,
AND EDUCATIONAL TESTING SERVICE
, 2002
"... The paper surveys 15 years of progress in three psychometric research areas: latent dimensionality structure, test fairness, and skills diagnosis of educational tests. It is proposed that one effective model for selecting and carrying out research is to chose one’s research questions from practical ..."
Abstract
 Add to MetaCart
The paper surveys 15 years of progress in three psychometric research areas: latent dimensionality structure, test fairness, and skills diagnosis of educational tests. It is proposed that one effective model for selecting and carrying out research is to chose one’s research questions from practical challenges facing educational testing, then bring to bear sophisticated probability modeling and statistical analyses to solve these questions, and finally to make effectiveness of the research answers in meeting the educational testing challenges be the ultimate criterion for judging the value of the research. The problemsolving power and the joy of working with a dedicated, focused, and collegial group of colleagues is emphasized. Finally, it is suggested that the summative assessment testing paradigm that has driven test measurement research for over half a century is giving way to a new paradigm that in addition embraces skills level formative assessment, opening up a plethora of challenging, exciting, and societally important research problems for psychometricians.