The technic of homogeneous tests compared with some aspects of "scale analysis" and factor analysis.

Loevinger, Jane

doi:10.1037/h0055827

Cited by 333 publications

(208 citation statements)

References 20 publications

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“…Guttman's coefficient of reproducibility has appeared to some reviewers (Loevinger,28;Festinger,13) as an ad hoc index with no mathematical rationale.…”

Section: How Is a Related ~O ~He Homogeneity Internal Consistency O~mentioning

confidence: 99%

Coefficient alpha and the internal structure of tests

1951

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A general formula (a) of which a special case is the KuderRichardson coefficient of equivalence is shown to be the mean of all split-half coefficients resulting from different splittings of a test. is therefore an estimate of the correlation between two random samples of items from a universe of items like those in the test. ~ is found to be an appropriate index of equivalence and, except for very short tests, of the first-factor concentration in the test. Tests divisible into distinct subtests should be so divided before using the formula. The index ~j, derived from a, is shown to be an index of inter-item homogeneity. Comparison is made to the Guttmau and Loevinger approaches. Parallel split coefficients are shown to be unnecessary for tests of common types. In designing tests, maximum interpretability of scores is obtained by increasing the firat-facter concentration in any separately-scored subtest and avoiding substantial group-factor clusters within a subtest. Scalability is not a requisite. I. Historical Resum~Any research based on measurement must be concerned with the accuracy or dependability or, as we usually call it, reliability of measurement. A reliability coefficient demonstrates whether the test designer was correct in expecting a certain collection of items to yield interpretable statements about individual differences (25).Even those investigators who regard reliability as a pale shadow of the more vital matter of validity cannot avoid considering the reliability of their measures. No validity coefficient and no factor analysis can be interpreted without some appropriate estimate of the magnitude of the error of measurement. The preferred way to find out how accurate one's measures are is to make two independent measurements and compare them. In practice, psychologists and educators have often not had the opportunity to recapture their subjects for a second test. Clinical tests, or those used for vocational guidance, are generally worked into a crowded schedule, and there is always a de-*The assistance of Dora Damrin and Willard Warrington is gratefully acknowledged. Miss Damrin took major responsibility for the empirical studies reported. This research was supported by the Bureau of Research and Service, College of Education. 297 298 PSYCHOMETRIKA sire to give additional tests if any extra time becomes available. Purely scientific investigations fare little better. It is hard enough to schedule twenty tests for a factorial study, let alone scheduling another twenty just to determine reliability.This difficulty was first circumvented by the invention of the splithail approach, whereby the test is rescored, half the items at a time, to get two estimates. The Spearman-Brown formula is then applied to get a coefficient similar to the correlation between two forms. The split-half Spearman-Brown procedure has been a standard method of test analysis for forty years. Alternative formulas have been developed, some of which have advantages over the original. In the course of our development, we shall re...

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“…Guttman's coefficient of reproducibility has appeared to some reviewers (Loevinger,28;Festinger,13) as an ad hoc index with no mathematical rationale.…”

Section: How Is a Related ~O ~He Homogeneity Internal Consistency O~mentioning

confidence: 99%

Coefficient alpha and the internal structure of tests

1951

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“…The H coefficient is due to Loevinger (1948), although she did not devise the H g and H gh coefficients. Mokken (1971) used H for scale construction and showed that it is useful for measuring the extent to which observed data approach the Guttman (1950) model and that it fulfills this role better than some alternative indices.…”

Section: Mokken Modelmentioning

confidence: 99%

Analyzing Psychopathology Items: A Case for Nonparametric Item Response Theory Modeling.

Meijer

Baneke

2004

Psychological Methods

190

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The authors discuss the applicability of nonparametric item response theory (IRT) models to the construction and psychometric analysis of personality and psychopathology scales, and they contrast these models with parametric IRT models. They describe the fit of nonparametric IRT to the Depression content scale of the Minnesota Multiphasic Personality Inventory-2 (J. N. Butcher, W. G. Dahlstrom, J. R. Graham, A. Tellegen, & B. Kaemmer, 1989). They also show how nonparametric IRT models can easily be applied and how misleading results from parametric IRT models can be avoided. They recommend the use of nonparametric IRT modeling prior to using parametric logistic models when investigating personality data.Recently, several authors have introduced and discussed the advantages of applying item response theory (IRT) models (e.g., Embretson & Reise, 2000) to construct personality 1 scales and to explore the structure of personality data sets. For example, Waller, Tellegen, McDonald, and Lykken (1996) contrasted the use of IRT with principalcomponent factor analysis, and Reise and Waller (2003) discussed the choice of an IRT model to analyze psychopathology-test data. That is, they compared the fit of the two-parameter and three-parameter logistic models (PLMs) on 15 unidimensional factor scales from the Minnesota Multiphasic Personality Inventory-Adolescent (MMPI-A; Butcher et al., 1992). Most studies apply parametric IRT models (in particular, the 2PLM and 3PLM) to investigate the quality of personality and psychopathology tests (e.g., Panter, Swygert, Dahlstrom, & Tanake, 1997;Robie, Zickar, & Schmitt, 2001;Steinberg, 1994;Waller, Thompson, & Wenk, 2000).The aim of the present study was to illustrate the usefulness of nonparametric IRT (NIRT) to construct and to analyze psychopathology and personality scales and tests. In our opinion, the use of NIRT has been underexposed in the recent personality literature (for an exception, see Santor & Ramsay, 1998). We show that these models are very suitable to exploring the psychometric properties of personality data. Interesting in this context is a study by Chernyshenko, Stark, Chan, Drasgow, and Williams (2001), who explored the use of NIRT modeling in personality measurement. Chernyshenko et al. fitted the 2PLM, the 3PLM, a graded response model, and Levine's nonparametric maximum-likelihood formula scoring models to dichotomous and polytomous data of the Sixteen Personality Factor Questionnaire (Conn & Rieke, 1994). They concluded that the nonparametric model provided the best fit of the models considered. Chernyshenko et al. and also Reise and Waller (2003) concluded that the response process underlying personality measurement is less well-understood than the response process in the cognitive domain. This being the case, we argue that using NIRT models based on exploring the simple covariance structure between items and based on nonparametric regression will lead to useful information that (a) can be interpreted very easily by practitioners, (b) avoids forcing the data ...

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“…군집분석에 관한 최근 연구로는 Warrens (2008), Choi 등 (2010), Lee와 Kim (2011), Yeo (2011), Park (2012Park ( , 2014aPark ( , 2014bPark ( , 2015, Lim과 Lim (2012) Table 2.1의 분할표를 이용하고자 한다. Loevinger (1947Loevinger ( , 1948 …”

Section: 서론unclassified

Bounds of PIM-based similarity measures with partially marginal proportion

Park¹

2015

Journal of the Korean Data and Information Science Society

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The technic of homogeneous tests compared with some aspects of "scale analysis" and factor analysis.

Cited by 333 publications

References 20 publications

Coefficient alpha and the internal structure of tests

Coefficient alpha and the internal structure of tests

Analyzing Psychopathology Items: A Case for Nonparametric Item Response Theory Modeling.

Bounds of PIM-based similarity measures with partially marginal proportion

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