Improving measurement models in clinical epidemiology: time to move beyond the inherent assumption of an underlying reflective measurement model

AbstractThe goal of reflective measurement model assessment is to ensure the reliability and validity of the construct measures and therefore provides support for the suitability of their inclusion in the path model. This chapter introduces the key criteria that are relevant in reflective measurement model assessment: indicator reliability, internal consistency reliability (Cronbach’s alpha, reliability coefficient rhoA, and composite reliability rhoC), convergent validity, and discriminant validity. We illustrate their use by means of the SEMinR package and a well-known model on corporate reputation.

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Measuring the Refined Theory of Individual Values in 49 Cultural Groups: Psychometrics of the Revised Portrait Value Questionnaire

Assessment ◽

10.1177/1073191121998760 ◽

2021 ◽

pp. 107319112199876

Author(s):

Shalom H. Schwartz ◽

Jan Cieciuch

Keyword(s):

Measurement Model ◽

Scaling Analysis ◽

Refined Theory ◽

Cultural Groups ◽

Individual Values ◽

Internal Reliability ◽

Measurement Models ◽

Circular Structure ◽

Almost All ◽

Portrait Value Questionnaire

Researchers around the world are applying the recently revised Portrait Value Questionnaire (PVQ-RR) to measure the 19 values in Schwartz’s refined values theory. We assessed the internal reliability, circular structure, measurement model, and measurement invariance of values measured by this questionnaire across 49 cultural groups ( N = 53,472) and 32 language versions. The PVQ-RR reliably measured 15 of the 19 values in the vast majority of groups and two others in most groups. The fit of the theory-based measurement models supported the differentiation of almost all values in every cultural group. Almost all values were measured invariantly across groups at the configural and metric level. A multidimensional scaling analysis revealed that the PVQ-RR perfectly reproduced the theorized order of the 19 values around the circle across groups. The current study established the PVQ-RR as a sound instrument to measure and to compare the hierarchies and correlates of values across cultures.

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

Construction Innovation ◽

10.1108/ci-06-2013-0029 ◽

2014 ◽

Vol 14 (2) ◽

pp. 229-244 ◽

Cited By ~ 5

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.

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Model Calibration for a Rigid Hexapod-Based End-Effector with Integrated Force Sensors

Sensors ◽

10.3390/s21103537 ◽

2021 ◽

Vol 21 (10) ◽

pp. 3537

Author(s):

Christian Friedrich ◽

Steffen Ihlenfeldt

Keyword(s):

Parameter Identification ◽

Degrees Of Freedom ◽

Force Measurement ◽

Experimental Studies ◽

Measurement Model ◽

Calibration Procedure ◽

Force Sensors ◽

End Effector ◽

Measurement Models ◽

Fast Procedure

Integrated single-axis force sensors allow an accurate and cost-efficient force measurement in 6 degrees of freedom for hexapod structures and kinematics. Depending on the sensor placement, the measurement is affected by internal forces that need to be compensated for by a measurement model. Since the parameters of the model can change during machine usage, a fast and easy calibration procedure is requested. This work studies parameter identification procedures for force measurement models on the example of a rigid hexapod-based end-effector. First, measurement and identification models are presented and parameter sensitivities are analysed. Next, two excitation strategies are applied and discussed: identification from quasi-static poses and identification from accelerated continuous trajectories. Both poses and trajectories are optimized by different criteria and evaluated in comparison. Finally, the procedures are validated by experimental studies with reference payloads. In conclusion, both strategies allow accurate parameter identification within a fast procedure in an operational machine state.

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Uncertainty quantiﬁcation for aerodynamic pressure probes, using adaptive quasi-Monte Carlo

Measurement Science and Technology ◽

10.1088/1361-6501/ac3f84 ◽

2021 ◽

Author(s):

Alexandros Christos Chasoglou ◽

Panagiotis Tsirikoglou ◽

Anestis I Kalfas ◽

Reza S Abhari

Keyword(s):

Monte Carlo ◽

Measurement Model ◽

Fast Response ◽

Two Stage ◽

Detailed Measurement ◽

Underlying Distribution ◽

Factors Affecting ◽

Quasi Monte Carlo ◽

Measurement Models ◽

Aerodynamic Pressure

Abstract In the present study, an adaptive randomized Quasi Monte Carlo methodology is presented, combining Stein’s two-stage adaptive scheme and Low Discrepancy Sobol sequences. The method is used for the propagation and calculation of uncertainties related to aerodynamic pneumatic probes and high frequency fast response aerodynamic probes (FRAP). The proposed methodology allows the fast and accurate, in a probabilistic sense, calculation of uncertainties, ensuring that the total number of Monte Carlo (MC) trials is kept low based on the desired numerical accuracy. Thus, this method is well-suited for aerodynamic pressure probes, where multiple points are evaluated in their calibration space. Complete and detailed measurement models are presented for both a pneumatic probe and FRAP. The models are segregated in sub-problems allowing the evaluation and inspection of intermediate steps of MC in a transparent manner, also enabling the calculation of the relative contributions of the elemental uncertainties on the measured quantities. Various, commonly used sampling techniques for MC simulation and different adaptive MC schemes are compared, using both theoretical toy distributions and actual examples from aerodynamic probes' measurement models. The robustness of Stein's two-stage scheme is demonstrated even in cases when signiffcant deviation from normality is observed in the underlying distribution of the output of the MC. With regards to FRAP, two issues related to piezo-resistive sensors are addressed, namely temperature dependent pressure hysteresis and temporal sensor drift, and their uncertainties are accounted for in the measurement model. These effects are the most dominant factors, affecting all flow quantities' uncertainties, with signiffcance that varies mainly with Mach and operating temperature. This work highlights the need to construct accurate and detailed measurement models for aerodynamic probes, that otherwise will result in signiffcant underestimation (in most cases in excess of 50%) of the final uncertainties.

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Exploring competitiveness and wellbeing in Italy by spatial principal component analysis

10.36253/978-88-5518-461-8.27 ◽

2021 ◽

pp. 141-146

Author(s):

Carlo Cusatelli ◽

Massimiliano Giacalone ◽

Eugenia Nissi

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Well Being ◽

Component Analysis ◽

Measurement Model ◽

Statistical Technique ◽

Multivariate Statistical ◽

Spatial Principal Component Analysis ◽

Italian Provinces ◽

Reflective Measurement

Well being is a multidimensional phenomenon, that cannot be measured by a single descriptive indicator and that, it should be represented by multiple dimensions. It requires, to be measured by combination of different dimensions that can be considered together as components of the phenomenon. This combination can be obtained by applying methodologies knows as Composite Indicators (CIs). CIs are largely used to have a comprehensive view on a phenomenon that cannot be captured by a single indicator. Principal Component Analysis (PCA) is one of the most popular multivariate statistical technique used for reducing data with many dimension, and often well being indicators are obtained using PCA. PCA is implicitly based on a reflective measurement model that it non suitable for all types of indicators. Mazziotta and Pareto (2013) in their paper discuss the use and misuse of PCA for measuring well-being. The classical PCA is not suitable for data collected on the territory because it does not take into account the spatial autocorrelation present in the data. The aim of this paper is to propose the use of Spatial Principal Component Analysis for measuring well being in the Italian Provinces.

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Simultaneous Measurement of 6DOF Motion Errors of Linear Guides of CNC Machine Tools Using Different Modes

Sensors ◽

10.3390/s20123439 ◽

2020 ◽

Vol 20 (12) ◽

pp. 3439

Author(s):

Peizhi Jia ◽

Bin Zhang ◽

Qibo Feng ◽

Fajia Zheng

Keyword(s):

Machine Tools ◽

Degrees Of Freedom ◽

Measurement Model ◽

Cnc Machine Tools ◽

Cnc Machine ◽

Motion Error ◽

Actual Measurement ◽

Measurement Models ◽

Measurement Head ◽

Measurement Mode

Based on the prior work on the six degrees of freedom (6DOF) motion errors measurement system for linear axes, and for the different types of machine tools and different installation methods, this study used a ray tracing idea to establish the measurement models for two different measurement modes: (1) the measurement head is fixed and the target mirror moves and (2) the target mirror is fixed and the measurement head moves. Several experiments were performed on the same linear guide using two different measurement modes. The comparative experiments show that the two measurement modes and their corresponding measurement models are correct and effective. In the actual measurement process, it is therefore possible to select the corresponding measurement model according to the measurement mode. Furthermore, the correct motion error evaluation results can be obtained.

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An Empirical Study on Career Choices Among Undergraduates: A PLS-SEM Hierarchical Component Model (HCM) Approach

International Journal of Human Resource Studies ◽

10.5296/ijhrs.v9i2.14841 ◽

2019 ◽

Vol 9 (2) ◽

pp. 276

Author(s):

Siew Chin Wong ◽

Jia Ying Lim ◽

Chui Seong Lim ◽

Kay Tze Hong

Keyword(s):

Peer Influence ◽

Career Choices ◽

Measurement Model ◽

Partial Least Square ◽

Least Square ◽

Component Model ◽

Peer Influences ◽

Future Research ◽

Measurement Models ◽

Hierarchical Component Model

This study examines how undergraduates’ personality, parental and peer influences on their career choice. Partial Least Square, hierarchical component model (HCM) was used to measure the formative measurement model of personality construct and reflective measurement models of parent and peer influence constructs on career choices in the study. Data were collected from 218 of undergraduates from local private and public universities. Findings show that there are significant positive relationship between personality, parental and peer influences and career choices. Such insights are useful for HRD practitioners to develop relevant HRD interventions to assist individuals and organizations in career development. Limitations and suggestions for future research are also discussed.

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Reliability and Model Fit

Educational and Psychological Measurement ◽

10.1177/0013164416638900 ◽

2016 ◽

Vol 76 (6) ◽

pp. 976-985 ◽

Cited By ~ 8

Author(s):

Leanne M. Stanley ◽

Michael C. Edwards

Keyword(s):

Test Scores ◽

Classical Test Theory ◽

Measurement Model ◽

Test Theory ◽

Model Fit ◽

Measurement Information ◽

Measurement Models ◽

Patient Reported ◽

Anxiety Item ◽

Psychometric Measurement

The purpose of this article is to highlight the distinction between the reliability of test scores and the fit of psychometric measurement models, reminding readers why it is important to consider both when evaluating whether test scores are valid for a proposed interpretation and/or use. It is often the case that an investigator judges both the reliability of scores and the fit of a corresponding measurement model to be either acceptable or unacceptable for a given situation, but these are not the only possible outcomes. This article focuses on situations in which model fit is deemed acceptable, but reliability is not. Data were simulated based on the item characteristics of the PROMIS (Patient Reported Outcomes Measurement Information System) anxiety item bank and analyzed using methods from classical test theory, factor analysis, and item response theory. Analytic techniques from different psychometric traditions were used to illustrate that reliability and model fit are distinct, and that disagreement among indices of reliability and model fit may provide important information bearing on a particular validity argument, independent of the data analytic techniques chosen for a particular research application. We conclude by discussing the important information gleaned from the assessment of reliability and model fit.

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A Large-Scale Test of the Replicability and Generalizability of Survey Measures in Close Relationship and Sexuality Science

10.31234/osf.io/d47q2 ◽

2019 ◽

Cited By ~ 1

Author(s):

Stephanie Gauvin ◽

Kathleen Merwin ◽

Chelsea Kilimnik ◽

Jessica A. Maxwell ◽

John Kitchener Sakaluk

Keyword(s):

Romantic Relationships ◽

Large Scale ◽

Measurement Model ◽

Large Sample ◽

Clinical Assessments ◽

Measurement Models ◽

Close Relationship ◽

Scale Test ◽

Structure Measurement

When measurement models are not replicable and/or generalizable, clinical assessments become of questionable utility, and unreplicable findings from studies using those measures will follow. Inspired by recent examinations of measurement in neighboring fields of psychology, we propose a Registered Report, in order to evaluate the replicability and generalizability of 20 well-known and emerging measures assessing elements of romantic relationships and sexuality. After collecting a large sample of that is both sexually and relationally diverse, we will evaluate the taxometric structure, measurement model replicability, reliability, and generalizability of each measure across a multitude of theorized sources of noninvariance. Our results are likely to be of high value to clinical researchers and practitioners alike, as we identify which measures can produce credible assessments, while simultaneously revealing measures with limited replicability and/or generalizability, as well as relational and sexual concepts for which groups may have radically different mental constructions.

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