Conditional standard error of measurement and personality scale scores: an investigation of classical test theory estimates with four MMPI scales

2001 ◽  
Vol 30 (4) ◽  
pp. 691-698
Author(s):  
Robert Saltstone ◽  
Colin Skinner ◽  
Paul Tremblay
Keyword(s):  
Standard Error ◽  
Classical Test Theory ◽  
Test Theory ◽  
Personality Scale ◽  
Classical Test ◽  
Scale Scores ◽  
Standard Error Of Measurement ◽  
Error Of Measurement

Examining the Psychometric Equivalency of MMPI-3 Scale Scores Derived From the MMPI-3 and the MMPI-2-RF-EX

Assessment ◽  
2021 ◽  
pp. 107319112199192
Author(s):  
Jordan T. Hall ◽  
William H. Menton ◽  
Yossef S. Ben-Porath
Keyword(s):  
Standard Error ◽  
External Validity ◽  
Minnesota Multiphasic Personality Inventory ◽  
Time Interval ◽  
Vector Correlations ◽  
Two Samples ◽  
Scale Scores ◽  
Test Version ◽  
Standard Error Of Measurement ◽  
Error Of Measurement

The current study evaluated the comparability of Minnesota Multiphasic Personality Inventory–3 (MMPI-3) scale scores derived from the 335-item MMPI-3 to MMPI-3 scale scores derived from the 433-item MMPI-2 restructured form–expanded version (MMPI-2-RF-EX), an enhanced version of the MMPI-2-RF that was used to develop and validate the MMPI-3. To that end, we examined data from 192 college undergraduates who completed both the MMPI-3 and MMPI-2-RF-EX 1 week apart using a counterbalanced design. Across versions, mean T-scores and standard deviations, estimates of internal consistency, and standard error of measurement values, were highly similar, indicating no clinically meaningful differences across versions. We also compared between-version test–retest comparability values with within-version values calculated using a sample of undergraduates ( N = 318) who completed the MMPI-2-RF-EX twice over the same time interval, finding only marginal differences across the two samples. Finally, we computed column-vector correlations between MMPI-3 scores from both versions and several criterion measures, where results reflected no effect of test version on external validity. Overall, we determined that scale scores derived from either booklet are psychometrically interchangeable, indicating that MMPI-3 scale scores obtained from an administration of the MMPI-2-RF-EX can be applied when using the 335-item MMPI-3.

scholarly journals What do Temkin's simulations of reliable change tell us?

2004 ◽  
Vol 10 (6) ◽  
pp. 902-903
Author(s):  
GERARD H. MAASSEN
Keyword(s):  
Standard Error ◽  
Classical Test Theory ◽  
Test Theory ◽  
Practice Effects ◽  
Reliable Change ◽  
Historical Aspect ◽  
Classical Test ◽  
Classic Approach ◽  
Post Hoc

Due to space limitations I have chosen to confine my reply to the comments by Temkin (this issue, pp. 899–901) that touch most directly the concepts of practice effects and reliable change. Temkin seems to portray my adherence to the classic approach as a private affair. However, Temkin herself (Temkin et al., 1999) reported to utilize the most widely applied procedures of Jacobson and Truax and of Chelune et al., which are based on the classic approach. For unexplained reasons they had substituted a different standard error. The unsatisfactory justification later given in their reply to Hinton-Bayre's (2000) letter revealed the presumably actual reason: unfamiliarity with psychometrics including the classical test theory (CTT). Not surprisingly, Temkin ignores this historical aspect in her comment. Nevertheless, the new post-hoc arguments she brings up deserve, of course, a fair evaluation.

scholarly journals Chyba měření a odhad pravého skóru: Připomenutí některých postupů Klasické testové teorie

TESTFÓRUM ◽  
2015 ◽  
Vol 4 (6) ◽  
pp. 67-84
Author(s):  
Hynek Cígler ◽  
Martin Šmíra
Keyword(s):  
Confidence Intervals ◽  
Classical Test Theory ◽  
Psychological Tests ◽  
Test Theory ◽  
Standard Errors ◽  
True Score ◽  
Paper Briefly ◽  
Classical Test ◽  
Test Developer ◽  
Error Of Measurement

Práce s chybou měření patří k základním dovednostem při interpretaci výsledků psychologických výsledků. Bohužel, řada českých psychologických metod však neobsahuje veškeré informace o chybě měření, například intervaly spolehlivosti či odhad standardní chyby měření pro různá použití. I v případě, že tyto informace jsou dostupné, je často nutné zvážit i další okolnosti a způsob výpočtu přizpůsobit – ne vždy je přitom možné se spolehnout na informace poskytnuté distributorem testu. Ani v současné počítačové době navíc nejsou jednoduše dostupné příslušné aplikace a řadu základních výpočtů by si tak psycholog v ideálním případě měl umět provést sám. Článek v krátkosti shrne běžné postupy při interpretaci chyby měření s využitím intervalů spolehlivosti v rámci klasické testové teorie, a to včetně podrobných příkladů, aby text mohl sloužit jako návod pro psychology z praxe. Cígler, H., & Šmíra, M.: Error of measurement and the estimation of true score: Selected methods of Classical test theoryOne of the elementary skills involved in the interpretation of the psychological results is handling the error of measurement. Unfortunately, many Czech psychological tests do not include all the necessary information about the error of measurement (e.g. confidence intervals and standard errors of measurement for different purposes). Even if such information is available, we might need to consider other circumstances of the assessment, and adjust the method of estimation and its application properly – it is not always possible to rely on the test developer in such cases. Since there are not many applications for such computations easily available for the test users, they should be capable of doing many of the elementary computations by hand. This paper briefly summarizes common techniques for the interpretation of the error of measurement using confidence intervals in the framework of Classical Test Theory. The theory is supported by detailed examples that should be helpful for applying these procedures in practice.

scholarly journals The comparison of the scores obtained by Bayesian nonparametric model and classical test theory methods

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110283
Author(s):  
Meltem Yurtcu ◽  
Hülya Kelecioglu ◽  
Edward L Boone
Keyword(s):  
Classical Test Theory ◽  
Small Sample ◽  
Test Theory ◽  
Nonparametric Model ◽  
Bayesian Nonparametric ◽  
Test Equating ◽  
Classical Test ◽  
A Value ◽  
Item Functioning ◽  
The Individual

Bayesian Nonparametric (BNP) modelling can be used to obtain more detailed information in test equating studies and to increase the accuracy of equating by accounting for covariates. In this study, two covariates are included in the equating under the Bayes nonparametric model, one is continuous, and the other is discrete. Scores equated with this model were obtained for a single group design for a small group in the study. The equated scores obtained with the model were compared with the mean and linear equating methods in the Classical Test Theory. Considering the equated scores obtained from three different methods, it was found that the equated scores obtained with the BNP model produced a distribution closer to the target test. Even the classical methods will give a good result with the smallest error when using a small sample, making equating studies valuable. The inclusion of the covariates in the model in the classical test equating process is based on some assumptions and cannot be achieved especially using small groups. The BNP model will be more beneficial than using frequentist methods, regardless of this limitation. Information about booklets and variables can be obtained from the distributors and equated scores that obtained with the BNP model. In this case, it makes it possible to compare sub-categories. This can be expressed as indicating the presence of differential item functioning (DIF). Therefore, the BNP model can be used actively in test equating studies, and it provides an opportunity to examine the characteristics of the individual participants at the same time. Thus, it allows test equating even in a small sample and offers the opportunity to reach a value closer to the scores in the target test.

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