Technical aspects of Muthén's liscomp approach to estimation of latent variable relations with a comprehensive measurement model

Psychometrika ◽  
1995 ◽  
Vol 60 (4) ◽  
pp. 489-503 ◽  
Author(s):  
Bengt O. Muthén ◽  
Albert Satorra
Keyword(s):  
Latent Variable ◽  
Measurement Model ◽  
Technical Aspects ◽  
Comprehensive Measurement

Aspects of project learning in construction: a socio-technical model

2014 ◽  
Vol 14 (2) ◽  
pp. 229-244 ◽  
Author(s):  
Ali Mohammed Alashwal ◽  
Hamzah Abdul-Rahman
Keyword(s):  
Latent Variable ◽  
Construction Projects ◽  
Team Building ◽  
Principal Component ◽  
Measurement Model ◽  
Survey Method ◽  
Path Modeling ◽  
Content Type ◽  
Measurement Models ◽  
Project Learning

Purpose – The purpose of this paper is to determine the measurement constructs of learning within construction projects' milieu. The literature indicated some mechanisms of learning in projects under four aspects, namely knowledge sharing, knowledge creation, team action to learn, and learning support. The empirical study attempts to verify whether intra-project learning can be measured through these aspects. Design/methodology/approach – The study used a survey method to collect the data from 36 mega-sized building projects in Malaysia. In total, 203 questionnaires were collected from professionals working in the sites of these projects. The data were analysed using principal component analysis (PCA) to determine the constructs of intra-project learning. Partial least squares-path modeling was used then to confirm the results of PCA and determine the contribution of each construct to intra-project learning. Findings – The results affirmed two constructs of intra-project learning, named, social and technical and each consisted of four indicators of learning. Originality/value – The paper emphasized the socio-technical perspective of learning and contributed to developing a hierarchical measurement model of learning in construction project. A project manager can propose new initiatives in response to the new perspective of learning for team building and continuous development. Lastly, the paper provides a comprehensive presentation of how to estimate the hierarchical measurement models of project learning as a latent variable.

Underlying Common Factors of Adolescent Problem Behaviors

2002 ◽  
Vol 29 (2) ◽  
pp. 161-182 ◽  
Author(s):  
Lening Zhang ◽  
John W. Welte ◽  
William F. Wieczorek
Keyword(s):  
Problem Behaviors ◽  
Latent Variable ◽  
Factor Model ◽  
Common Factor ◽  
Measurement Model ◽  
First Order ◽  
Adolescent Problem Behaviors ◽  
The Common ◽  
Order Factor ◽  
Second Order Factor Analysis

The Buffalo Longitudinal Study of Young Men was used to address the possibility of a common factor underlying adolescent problem behaviors. First, a measurement model with a single first-order factor was compared to a model with three separate correlated first-order factors. The three-factor model was better supported, making it logical to conduct a second-order factor analysis, which confirmed the logic. Second, a substantive model was estimated in each of two waves with psychopathic state as the common factor predicting drinking, drug use, and delinquency. Psychopathic state was stable across waves. The theory that a single latent variable accounts for large covariance among adolescent problem behaviors was supported.

Towards a further step in understanding business excellence models: a comparative approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammed Hamdan Alanazi
Keyword(s):  
Relevant Literature ◽  
Measurement Model ◽  
Comparative Approach ◽  
Cultural Economic ◽  
Content Type ◽  
Business Excellence ◽  
Phase Study ◽  
National Quality ◽  
Quality Award ◽  
Comprehensive Measurement

PurposeA comparative analysis of the validity of business excellence models (BEMs) has rarely been empirically pursued. In addition to their similarities, BEMs exhibit differences in terms of their criteria, relations and emphasis, and some researchers have claimed that it is because these models tend to represent underlying cultural, economic, or social dynamics, as well as global best practices. Based on three such BEMs (the Malcolm Baldrige National Quality Award (MBNQA) model, the European Foundation for Quality Management (EFQM) model and the King Abdul Aziz Quality Award (KAQA) model), this paper introduces a four-phase study to analyse these models comparatively.Design/methodology/approachThis paper: (1) conceptually delineates the distinctive natures of and differences between the three models; (2) develops a comprehensive measurement model based on the content of these models; (3) reviews the relevant literature on BEMs; (4) discusses the motivation behind this comparative approach and (5) introduces a four-phase study to comparatively analyse these models.FindingsA comprehensive measurement model and three structural models are developed, but empirical tests have not been performed. This developed approach is introduced here as a first step in the advancement of our understanding of BEMs and their underlying theory.Originality/valueThe range of variability and complexity of BEMs—i.e. a holistic and comparative empirical view of BEMs—have not so far been fully considered, and findings in this domain tend to be inclusive, while some of the underlying relations of these models have not been investigated. This paper contributes to filling these research gaps.

The Structure, Specificity, and Validity of Depression Symptoms

2017 ◽  
pp. 61-86
Author(s):  
David Watson ◽  
Michael W. O’Hara
Keyword(s):  
Major Depression ◽  
Discriminant Validity ◽  
Measurement Model ◽  
Criterion Validity ◽  
Depression Symptoms ◽  
Symptom Dimensions ◽  
Convergent And Discriminant Validity ◽  
Specific Symptoms ◽  
Comprehensive Measurement ◽  
Symptom Criteria

This chapter examines key symptom criteria of major depression. It begins by developing a comprehensive measurement model based on six symptom dimensions: dysphoria, lassitude, insomnia, suicidality, appetite loss, and appetite gain. It then demonstrates that these symptom dimensions are robust and show impressive convergent and discriminant validity across multiple methods (self-reports, clinicians’ ratings, interview assessments). Three types of symptoms—dysphoria, lassitude, and suicidality—exhibit strong criterion validity and significant specificity in relation to diagnoses of major depression. In contrast, symptoms of insomnia and appetite disturbance display unimpressive criterion validity and poor specificity. Moreover, these nonspecific symptoms provided little or no incremental information in logistic regression analyses. Taken together, these results suggest that the diagnosis of depression can be improved by focusing primarily on strong and specific symptoms (such as dysphoria and lassitude) and deemphasizing weak and nonspecific symptoms (i.e., insomnia and appetite disturbance).

Introducingν-CLEAR: a latent variable approach to measuring nuclear proficiency

2018 ◽  
Vol 37 (2) ◽  
pp. 232-256 ◽  
Author(s):  
Bradley C. Smith ◽  
William Spaniel
Keyword(s):  
Measurement Error ◽  
International Relations ◽  
Latent Variable ◽  
Measurement Model ◽  
Statistical Measurement ◽  
Variable Approach ◽  
Latent Variable Approach

The causes and consequences of nuclear proficiency are central to important questions in international relations. At present, researchers tend to use observable characteristics as a proxy. However, aggregation is a problem: existing measures implicitly assume that each indicator is equally informative and that measurement error is not a concern. We overcome these issues by applying a statistical measurement model to directly estimate nuclear proficiency from observed indicators. The resulting estimates form a new dataset on nuclear proficiency which we call ν-CLEAR. We demonstrate that these estimates are consistent with known patterns of nuclear proficiency while also uncovering more nuance than existing measures. Additionally, we demonstrate how scholars can use these estimates to account for measurement error by revisiting existing results with our measure.

scholarly journals The V-Dem Measurement Model: Latent Variable Analysis for Cross-National and Cross-Temporal Expert-Coded Data​

2019 ◽  
Author(s):  
Daniel Pemstein ◽  
Kyle L. Marquardt ◽  
Eitan Tzelgov ◽  
Yi-ting Wang ◽  
Juraj Medzihorsky ◽  
...  
Keyword(s):  
Latent Variable ◽  
Measurement Model ◽  
Latent Variable Analysis ◽  
Variable Analysis ◽  
Cross National

scholarly journals Psychometric Models of Individual Differences in Reading Comprehension: A Reanalysis of Freed, Hamilton, and Long (2017)

2019 ◽  
Author(s):  
Sara Anne Goring ◽  
Christopher J. Schmank ◽  
Michael J. Kane ◽  
Andrew R. A. Conway
Keyword(s):  
Reading Comprehension ◽  
Individual Differences ◽  
Cognitive Abilities ◽  
Latent Variable ◽  
Convergent Validity ◽  
Cognitive Task ◽  
Network Modeling ◽  
Network Models ◽  
Measurement Model ◽  
Common Cause

Individual differences in reading comprehension have often been explored using latent variable modeling (LVM), to assess the relative contribution of domain-general and domain-specific cognitive abilities. However, LVM is based on the assumption that the observed covariance among indicators of a construct is due to a common cause (i.e., a latent variable; Pearl, 2000). This is a questionable assumption when the indicator variables are measures of performance on complex cognitive tasks. According to Process Overlap Theory (POT; Kovacs & Conway, 2016), multiple processes are involved in cognitive task performance and the covariance among tasks is due to the overlap of processes across tasks. Instead of a single latent common cause, there are thought to be multiple dynamic manifest causes, consistent with an emerging view in psychometrics called network theory (Barabási, 2012; Borsboom & Cramer, 2013). In the current study, we reanalyzed data from Freed et al. (2017) and compared two modeling approaches: LVM (Study 1) and psychometric network modeling (Study 2). In Study 1, two exploratory LVMs demonstrated problems with the original measurement model proposed by Freed et al. Specifically, the model failed to achieve discriminant and convergent validity with respect to reading comprehension, language experience, and reasoning. In Study 2, two network models confirmed the problems found in Study 1, and also served as an example of how network modeling techniques can be used to study individual differences. In conclusion, more research, and a more informed approach to psychometric modeling, is needed to better understand individual differences in reading comprehension.

scholarly journals Prediksi Minat Perilaku Menggunakan Jasa Pajak Elektronik: Analisis Faktor Konfirmatori

InFestasi ◽  
2018 ◽  
Vol 13 (2) ◽  
pp. 321
Author(s):  
Jullie J. Sondakh
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Behavioral Intention ◽  
Latent Variable ◽  
Structural Equation ◽  
Structural Model ◽  
Measurement Model ◽  
Equation Modeling ◽  
Confirmatory Factor

<p class="Ventura-Abstract">The purpose of this research is to predict the tax payer behavioral intention of using the e-SPT through the application of Technology Acceptance Model (TAM).</p><p class="Ventura-Abstract">This research used survey method to collect primary data from the population of tax payer in the city of Manado and Bitung with 156 respondents while using judgement sampling method.The data analysis is using Structural Equation Modeling (SEM) that consists of two steps; the measurement model and structural model. The focus of this research is on the first step of SEM modeling, which is the measurement model by using the Confirmatory Factor Analysis (CFA). The purpose of this analysis is to test the validity and reliability from the indicator of the construct or latent variable researched, thus, we will obtain the fit construct or latent variable before proceeding to the next step of SEM which is the structural model.Based on the confirmatory factor analysis (CFA), we obtained the validity test result, convergent validity, and reliability test result, construct reliability and variance extracted, from the indicator of construct or latent variable which are perceived usefulness, perceived ease of use, attitude towards e-SPT, and behavioral intention to use e-SPT. The reliabilty and validity test result showed that there is no indicator from all the tested latent variable to be excluded for the next step of Structural Equation Modeling (SEM)  which is the structural model.</p><p class="Ventura-Abstract"> </p><p class="Ventura-Abstract">Tujuan penelitian ini adalah melakukan prediksi minat perilaku wajib pajak menggunakan  e-SPT melalui penerapanTechnology Acceptance Model (TAM). Penelitian ini menggunakan metode survei untuk mengumpulkan data primer dari populasi yaitu wajib pajak di Kota Manado dan Bitung dengan jumlah sampel sebanyak 156 responden serta penentuan sampel berdasarkan metode  judgment sampling. Teknik analisis data menggunakan pemodelan Structural Equation Modeling (SEM) yang terdiri  dari dua tahapan yaitu model pengukuran (measurement model) dan model struktural (structural model). Fokus penelitian ini adalah pada pemodelan SEM tahap pertama yaitu model pengukuran (measurement model)  melalui  analisis faktor konfirmatori (Confirmatory Factor Analysis - CFA). Analisis ini  bertujuan  untuk menguji validitas dan reliabilitas dari indikator-indikator pembentuk konstruk atau variabel laten yang diteliti sehingga diperoleh  konstruk atau variabel laten yang fit  sebelum lanjut ke tahap pemodelan SEM berikutnya  yaitu model struktural. Berdasarkan analisis faktor konfirmatori (Confirmatory Factor Analysis - CFA) diperoleh hasil uji validitas yaitu signifikansi  factor loading (convergent validity) dan reliabilitas (construct reliability dan variance extracted) dari indikator pembentuk konstruk atau variabel laten kegunaan persepsian (Perceived Usefulness), kemudahan penggunaan persepsian (Perceived ease of use), sikap terhadap penggunaan  e-SPT (Attitude towards e-SPT) dan  minat perilaku  menggunakan e-SPT (Behavioral intention to use e-SPT). Hasil uji validitas dan reliabilitas ini menunjukan bahwa tidak ada indikator dari variabel kegunaan persepsian (Perceived Usefulness), kemudahan penggunaan persepsian (Perceived ease of use), sikap terhadap penggunaan  e-SPT (Attitude towards e-SPT) dan  minat perilaku  menggunakan e-SPT (Behavioral intention to use e-SPT) yang di hilangkan pada analisis selanjutnya yaitu pemodelan Structural Equation Modeling (SEM) tahap kedua  sehingga  dapat dilakukan estimasi model persamaan struktural (structural model).</p>

scholarly journals A new approach to measuring absolute pitch on a psychometric theory of isolated pitch perception: Is it disentangling specific groups or capturing a continuous ability?

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247473
Author(s):  
Nayana Di Giuseppe Germano ◽  
Hugo Cogo-Moreira ◽  
Fausto Coutinho-Lourenço ◽  
Graziela Bortz
Keyword(s):  
Latent Variable ◽  
Latent Class ◽  
Latent Trait ◽  
Absolute Pitch ◽  
Measurement Model ◽  
Model Fit ◽  
Latent Variable Model ◽  
Variable Model ◽  
New Approach ◽  
Information Indices

Absolute Pitch (AP) is commonly defined as a rare ability that allows an individual to identify any pitch by name. Most researchers use classificatory tests for AP which tracks the number of isolated correct answers. However, each researcher chooses their own procedure for what should be considered correct or incorrect in measuring this ability. Consequently, it is impossible to evaluate comparatively how the stimuli and criteria classify individuals in the same way. We thus adopted a psychometric perspective, approaching AP as a latent trait. Via the Latent Variable Model, we evaluated the consistency and validity for a measure to test for AP ability. A total of 783 undergraduate music students participated in the test. The test battery comprised 10 isolated pitches. All collected data were analyzed with two different rating criteria (perfect and imperfect) under three Latent Variable Model approaches: continuous (Item Response Theory with two and three parameters), categorical (Latent Class Analysis), and the Hybrid model. According to model fit information indices, the perfect approach (only exact pitch responses as correct) measurement model had a better fit under the trait (continuous) specification. This contradicts the usual assumption of a division between AP and non-AP possessors. Alternatively, the categorical solution for the two classes demonstrated the best solution for the imperfect approach (exact pitch responses and semitone deviations considered as correct).

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