Latent Class Analysis: A General Solution and an Empirical Evaluation

Green, Bert F.

doi:10.1002/j.2333-8504.1951.tb00215.x

Cited by 3 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The emphasis of Green (1950aGreen ( , b, 1951aGreen ( , b, 1952 was on analyzing item response data using latent structure (LS) and latent class (LC) models. Green (1951b) …”

Section: Some Early Work Leading Up To Irt (1940s and 1950s)mentioning

confidence: 99%

Item Response Theory

Carlson

Davier

2017

Methodology of Educational Measurement and Assessment

View full text Add to dashboard Cite

Item response theory (IRT) models, in their many forms, are undoubtedly the most widely used models in large-scale operational assessment programs. They have grown from negligible usage prior to the 1980s to almost universal usage in largescale assessment programs, not only in the United States, but in many other countries with active and up-to-date programs of research in the area of psychometrics and educational measurement.Perhaps the most important feature leading to the dominance of IRT in operational programs is the characteristic of estimating individual item locations (difficulties) and test-taker locations (abilities) separately, but on the same scale, a feature not possible with classical measurement models. This estimation allows for tailoring tests through judicious item selection to achieve precise measurement for individual test takers (e.g., in computerized adaptive testing, CAT) or for defining important cut points on an assessment scale. It also provides mechanisms for placing different test forms on the same scale (linking and equating). Another important characteristic of IRT models is local independence: for a given location of test takers on the scale, the probability of success on any item is independent of that of every other item on that scale. This characteristic is the basis of the likelihood function used to estimate test takers' locations on the scale.Few would doubt that ETS researchers have contributed more to the general topic of IRT than individuals from any other institution. In this chapter we briefly review most of those contributions, dividing them into sections by decades of publication. Of course, many individuals in the field have changed positions between

show abstract

“…The emphasis of Green (1950aGreen ( , b, 1951aGreen ( , b, 1952 was on analyzing item response data using latent structure (LS) and latent class (LC) models. Green (1951b) …”

Section: Some Early Work Leading Up To Irt (1940s and 1950s)mentioning

confidence: 99%

Item Response Theory

Carlson

Davier

2017

Methodology of Educational Measurement and Assessment

View full text Add to dashboard Cite

show abstract

“…The emphasis of Green (1950aGreen ( /1951aGreen ( , 1950bGreen ( , 1950cGreen ( , 1950dGreen ( /1952Green ( , 1951b) was on analyzing item response data using latent structure (LS) and latent class (LC) models. Green (1951b)…”

Section: Some Early Work Leading Up To Irt (1940s and 1950s)mentioning

confidence: 99%

Item Response Theory

Carlson

Davier

2013

ETS Research Report Series

View full text Add to dashboard Cite

Few would doubt that ETS researchers have contributed more to the general topic of item response theory (IRT) than individuals from any other institution. In this report, we briefly review most of those contributions, dividing them into sections by decades of publication, beginning with early work by Fred Lord and Bert Green in the 1950s and ending with recent work that produced models involving complex structures and multiple dimensions.

show abstract

An application of confidence intervals and of maximum likelihood to the estimation of an examinee's ability

Lord

1953

Psychometrika

View full text Add to dashboard Cite

Latent Class Analysis: A General Solution and an Empirical Evaluation

Cited by 3 publications

References 9 publications

Item Response Theory

Item Response Theory

Item Response Theory

An application of confidence intervals and of maximum likelihood to the estimation of an examinee's ability

Contact Info

Product

Resources

About