scholarly journals Robustness of BW aberrance indices against test length

Many research had shown person fit indices might be influenced by the factor of test length on their detection rates of aberrant responses. The purpose of this study was to examine test length effects on the BW aberrance indices. Three conditions were designed in this study: test length (K, including 25, 50,100, and 200 items), ability ratio (T/K, defined as the total person score divided by test length K), and error ratio (E/K, defined as the number of errors within ability level divided by test length). Four 100-person times varying-item data matrices (100x25, 100x50, 100x100, and 100x200) were randomly generated and permuted 500 times for each data matrix through 20 repeats. Results showed that after partialling out the factors of E/K and T/K, the effect of test length on the association between the two indices was very slight. In nonlinear regression analyses, E/K and T/K can predict more than 76 and 73 percent of the variances of the B index and that of the W index, respectively, but test length with both very slight contributions on them. Furthermore, a very good model fit generated from SEM analyses also showed the effect of test length on the B and W indices were very tiny. All these pieces of evidence endorsed the B and W indices were robust with test length.

2017 ◽  
Vol 42 (5) ◽  
pp. 343-358
Author(s):  
Yan Xia ◽  
Yi Zheng

Snijders developed a family of person fit indices that asymptotically follow the standard normal distribution, when the ability parameter is estimated. So far, [Formula: see text], U*, W*, [Formula: see text], and [Formula: see text] from this family have been proposed in previous literature. One common property shared by [Formula: see text], U*, and W* (also [Formula: see text] and [Formula: see text] in some specific conditions) is that they employ symmetric weight functions and thus identify spurious scores on both easy and difficult items in the same manner. However, when the purpose is to detect only the spuriously high scores on difficult items, such as cheating, guessing, and having item preknowledge, using symmetric weight functions may jeopardize the detection rates of the target aberrant response patterns. By specifying two types of asymmetric weight functions, this study proposes SHa(λ)* (λ = 1/2 or 1) and SHb(β)* (β = 2 or 3) based on Snijders’s framework to specifically detect spuriously high scores on difficult items. Two simulation studies were carried out to investigate the Type I error rates and empirical power of SHa(λ)* and SHb(β)*, compared with [Formula: see text], U*, W*, [Formula: see text], and [Formula: see text]. The empirical results demonstrated satisfactory performance of the proposed indices. Recommendations were also made on the choice of different person fit indices based on specific purposes.


2019 ◽  
Vol 35 (1) ◽  
pp. 126-136 ◽  
Author(s):  
Tour Liu ◽  
Tian Lan ◽  
Tao Xin

Abstract. Random response is a very common aberrant response behavior in personality tests and may negatively affect the reliability, validity, or other analytical aspects of psychological assessment. Typically, researchers use a single person-fit index to identify random responses. This study recommends a three-step person-fit analysis procedure. Unlike the typical single person-fit methods, the three-step procedure identifies both global misfit and local misfit individuals using different person-fit indices. This procedure was able to identify more local misfit individuals than single-index method, and a graphical method was used to visualize those particular items in which random response behaviors appear. This method may be useful to researchers in that it will provide them with more information about response behaviors, allowing better evaluation of scale administration and development of more plausible explanations. Real data were used in this study instead of simulation data. In order to create real random responses, an experimental test administration was designed. Four different random response samples were produced using this experimental system.


Methodology ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 188-196 ◽  
Author(s):  
Esther T. Beierl ◽  
Markus Bühner ◽  
Moritz Heene

Abstract. Factorial validity is often assessed using confirmatory factor analysis. Model fit is commonly evaluated using the cutoff values for the fit indices proposed by Hu and Bentler (1999) . There is a body of research showing that those cutoff values cannot be generalized. Model fit does not only depend on the severity of misspecification, but also on nuisance parameters, which are independent of the misspecification. Using a simulation study, we demonstrate their influence on measures of model fit. We specified a severe misspecification, omitting a second factor, which signifies factorial invalidity. Measures of model fit showed only small misfit because nuisance parameters, magnitude of factor loadings and a balanced/imbalanced number of indicators per factor, also influenced the degree of misfit. Drawing from our results, we discuss challenges in the assessment of factorial validity.


2022 ◽  
Author(s):  
Neil Hester ◽  
Jordan Axt ◽  
Eric Hehman

Racial attitudes, beliefs, and motivations lie at the center of many of the most influential theories of prejudice and discrimination. The extent to which such theories can meaningfully explain behavior hinges on accurate measurement of these latent constructs. We evaluated the validity properties of 25 race-related scales in a sample of 1,031,207 respondents using modern approaches such as dynamic fit indices, Item Response Theory, and nomological nets. Despite showing adequate internal reliability, many scales demonstrated poor model fit and had latent score distributions showing clear floor or ceiling effects, results that illustrate deficiencies in measures’ ability to capture their intended construct. Nomological nets further suggested that the theoretical space of “racial prejudice” is crowded with scales that may not actually capture meaningfully distinct latent constructs. We provide concrete recommendations for scale selection and renovation and outline implications for overlooking measurement issues in the study of prejudice and discrimination.


2018 ◽  
Vol 15 (4) ◽  
pp. 2407
Author(s):  
Yeşim Bayrakdaroglu ◽  
Dursun Katkat

The purpose of this study is to research how marketing activities of international sports organizations are performed and to develop a scale determining the effects of image management on public. The audiences of interuniversity World Winter Olympic sheld in Erzurum in 2011 participated in the research. Explanatory and Confirmatory Factor Analysis, reliability analysis were performed over the data obtained. All model fit indices of 25-item and four-factor structure of quality-image scale perceived in sports organizations applied were found to be at good level. In line with the findings obtained from the explanatory and confirmatory factor analyses and reliability analysis, it can be uttered that the scale is a valid and reliable measurement tool that can be used in field researches.


Author(s):  
Khushbu Khurana ◽  
Rajnish Kumar Misra

The purpose of this study is to identify employability skills among aspiring engineering graduates and develop measurement scale to assess their skill sets. This research has been conducted in two phases: Phase 1 covers the scale development process and Phase 2 covers exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and validation. The findings of EFA resulted in ten factors of employability. Subsequently, CFA identified nine different factors: leadership, critical thinking, numeracy, sociability, using technology, planning and organizing, problem-solving, teamwork, and emotional intelligence skills. The values of CFA met the acceptance level of different fit indices and thus, resulted in a good model fit. Further, the internal consistency of the total scale yielded Cronbach's alpha value (α = 0.82). The threshold values of CR, AVE, and MSV also met the required criteria. Thus, it received a valid and reliable 26-item measurement scale of employability which can prove to be useful for academia, students, and employers in computer science and information technology.


2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S179-S179
Author(s):  
Mei San Ang ◽  
Gurpreet Rekhi ◽  
Jimmy Lee

Abstract Background The conceptualization of negative symptoms has been refined in the past decades. Two-factor model comprising Motivation and Pleasure (MAP) and Emotional Expressivity (EE), five-factor model representing five domains of negative symptoms and second-order five-factor model incorporating the two-factor and five-factor models (Anhedonia, Asociality and Avolition regressed on MAP; Blunted Affect and Alogia regressed on EE) have been suggested as latent structure of negative symptoms. In most studies, the item “Lack of Normal Distress” in the Brief Negative Symptom Scale (BNSS) did not fit well in factor models. Nevertheless, the reported correlation and item-total correlation of Distress with other negative symptom domains and BNSS items were not negligible. Emotion deficit was also discussed as a part of negative symptoms conceptualization. As a single item may not be sufficient to represent an underlying construct that is potentially abstract and complex, the Schedule for the Deficit Syndrome (SDS) which comprises “Diminished Emotional Range” that is conceptually relevant to the BNSS Distress was employed. The study aimed to reexamine the conceptualization of negative symptoms by examining the model fit of several models when BNSS Distress and SDS Emotion (EMO) were included in the models using confirmatory factor analyses (CFA). Methods Two-hundred and seventy-four schizophrenia outpatients aged 21–65 were assessed on the BNSS and SDS. In the two-factor models, Restricted Affect, Diminished Emotional Range and Poverty of Speech in SDS and all items in BNSS Blunted Affect and Alogia subscales were regressed on EE, Curbing of Interests, Diminished Sense of Purpose and Diminished Social Drive in SDS and all items in BNSS Anhedonia, Asociality and Avolition subscales were regressed on MAP, without EMO, or with EMO regressed on either EE or MAP. Five-factor models and second-order five-factor models were examined, with or without EMO. Lastly, a six-factor model with EMO manifested by the sixth factor and second-order six-factor models in which EMO was regressed on either EE or MAP were tested. Root mean square error of approximation (RMSEA) <0.08, comparative fit index (CFI) >0.95, the Tucker-Lewis Index (TLI) >0.95, and weighted root-mean-square residual (WRMR) <1.0 indicate good model fit. CFAs were conducted using Mplus version 7.4. Results The two-factor models did not yield adequate fit indices. Five-factor model and second-order five-factor model without EMO had good model fit; five-factor model: RMSEA=0.056 (0.044–0.068), CFI=0.996, TFI=0.995, WRMR=0.718; second-order five-factor model: RMSEA=0.049 (0.036–0.061), CFI=0.997, TFI=0.996, WRMR=0.758. When EMO was included as indicator in one of the factors in the five-factor models, only the model in which EMO was regressed on Alogia yielded adequate fit. Similarly, in the second-order five-factor models, adequate fit indices were observed only when EMO was regressed on Alogia and Blunted Affect. The six-factor model fitted the data well, RMSEA=0.053 (0.042–0.064), CFI=0.996, TFI=0.995, WRMR=0.711. Second-order six-factor model with EMO regressed on EE yielded better model fit than MAP, RMSEA=0.050 (0.039–0.061), CFI=0.996, TFI=0.995, WRMR=0.849. Discussion In line with previous studies, five-factor and second-order five-factor models without EMO fitted the data well. When EMO was included, a six-factor model and a second-order six-factor model in which the sixth factor was regressed on EE showed good model fit. Emotion, motivation and behavior are intertwined. Our results showed that diminished emotion may also be one of the components of negative symptoms, which had higher association with EE than MAP.


2018 ◽  
Vol 18 (3) ◽  
Author(s):  
Pablo Ezequiel Flores-Kanter ◽  
Sergio Dominguez-Lara ◽  
Mario Alberto Trógolo ◽  
Leonardo Adrián Medrano

<p>Bifactor models have gained increasing popularity in the literature concerned with personality, psychopathology and assessment. Empirical studies using bifactor analysis generally judge the estimated model using SEM model fit indices, which may lead to erroneous interpretations and conclusions. To address this problem, several researchers have proposed multiple criteria to assess bifactor models, such as a) conceptual grounds, b) overall model fit indices, and c) specific bifactor model indicators. In this article, we provide a brief summary of these criteria. An example using data gathered from a recently published research article is also provided to show how taking into account all criteria, rather than solely SEM model fit indices, may prevent researchers from drawing wrong conclusions.</p>


2019 ◽  
Vol 45 ◽  
Author(s):  
Pieter Schaap

Orientation: The rigid application of conventional confirmatory factor analysis (CFA) techniques, the overreliance on global model fit indices and the dismissal of the chi-square statistic appear to have an adverse impact on the research of psychological ownership measures.Research purpose: The purpose of this study was to explicate the South African Psychological Ownership Questionnaire’s (SAPOS’s) CFA model fit using the Bayesian structural equation modelling (BSEM) technique.Motivation for the study: The need to conduct this study derived from a renewed awareness of the incorrect use of the chi-square statistic and global fit indices of CFA in social sciences research.Research approach/design and method: The SAPOS measurement model fit was explicated on two study samples consisting, respectively, of 712 and 254 respondents who worked in various organisations in South Africa. A Bayesian approach to CFA was used to evaluate if local model misspecifications were substantive and justified the rejection of the SAPOS model.Main findings: The findings suggested that a rejection of the SAPOS measurement model based on the results of the chi-square statistic and global fit indices would be unrealistic and unfounded in terms of substantive test theory.Practical/managerial implications: BSEM appeared to be a valuable diagnostic tool to pinpoint and evaluate local CFA model misspecifications and their effect on a measurement model.Contribution/value-add: This study showed the importance of considering local misspecifications rather than only relying the chi-square statistic and global fit indices when evaluating model fit.


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