A robust alternative estimator for small to moderate sample SEM: Bias-corrected factor score path analysis

2019 ◽  
Vol 94 ◽  
pp. 83-98 ◽  
Author(s):  
Ben Kelcey
Keyword(s):  
Path Analysis ◽  
Factor Score ◽  
Alternative Estimator

Factor Score Path Analysis

Methodology ◽  
2017 ◽  
Vol 13 (Supplement 1) ◽  
pp. 31-38 ◽  
Author(s):  
Ines Devlieger ◽  
Yves Rosseel
Keyword(s):  
Path Analysis ◽  
Latent Variables ◽  
Structural Equation ◽  
Factor Score ◽  
Small Sample ◽  
Equation Modeling ◽  
Large Sample Size ◽  
Sample Sizes ◽  
Suitable Alternative ◽  
Step Factor

Abstract. Theoretical researchers consider Structural Equation Modeling (SEM) to be the preferred method to study the relationships among latent variables. However, SEM has the disadvantage of requiring a large sample size, especially if the model is complex. Furthermore, since SEM estimates all parameters simultaneously, one misspecification in the model may influence the whole model. For these reasons, applied researchers often use a two-step Factor Score Regression (FSR) approach. In the first step, factor scores are calculated for the latent variables, which are used to perform a linear regression in the second step. However, this method results in incorrect regression coefficients. Croon (2002) developed a method that corrects for this bias. We combine this method of Croon (2002) with path analysis, resulting in Factor Score Path Analysis. This method results in correct path coefficients and has some advantages over SEM: it requires smaller sample sizes, can handle more complex models and the method is less sensitive to misspecifications, because of its stepwise nature. In conclusion, this method can be a suitable alternative for SEM, when one is dealing with a complex model and small sample sizes.

scholarly journals Correction to: Medical specialists’ basic psychological needs, and motivation for work and lifelong learning: a two-step factor score path analysis

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Stéphanie M. E. van der Burgt ◽  
Rashmi A. Kusurkar ◽  
Janneke A. Wilschut ◽  
Sharon L. N. M. Tjin A Tsoi ◽  
Gerda Croiset ◽  
...  
Keyword(s):  
Path Analysis ◽  
Lifelong Learning ◽  
Factor Score ◽  
Psychological Needs ◽  
Basic Psychological Needs ◽  
Medical Specialists ◽  
Step Factor

scholarly journals Medical specialists’ basic psychological needs, and motivation for work and lifelong learning: a two-step factor score path analysis

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Stéphanie M. E. van der Burgt ◽  
Rashmi A. Kusurkar ◽  
Janneke A. Wilschut ◽  
Sharon L. N. M. Tjin A Tsoi ◽  
Gerda Croiset ◽  
...  
Keyword(s):  
Path Analysis ◽  
Lifelong Learning ◽  
Factor Score ◽  
Psychological Needs ◽  
Basic Psychological Needs ◽  
Medical Specialists ◽  
Step Factor

scholarly journals Croon’s Bias-Corrected Factor Score Path Analysis for Small- to Moderate-Sample Multilevel Structural Equation Models

2019 ◽  
Vol 24 (1) ◽  
pp. 55-77 ◽  
Author(s):  
Benjamin Kelcey ◽  
Kyle Cox ◽  
Nianbo Dong
Keyword(s):  
Maximum Likelihood ◽  
Path Analysis ◽  
Latent Variables ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Factor Score ◽  
Likelihood Estimation ◽  
Bias Error ◽  
Parameter Estimates ◽  
Multilevel Structural Equation

Maximum likelihood estimation of multilevel structural equation model (MLSEM) parameters is a preferred approach to probe theories involving latent variables in multilevel settings. Although maximum likelihood has many desirable properties, a major limitation is that it often fails to converge and can incur significant bias when implemented in studies with a small to moderate multilevel sample (e.g., fewer than 100 organizations with 10 or less individuals/organization). To address similar limitations in single-level SEM, literature has developed Croon’s bias-corrected factor score path analysis estimator that converges more regularly than maximum likelihood and delivers less biased parameter estimates with small to moderate sample sizes. We derive extensions to this framework for MLSEMs and probe the degree to which the estimator retains these advantages with small to moderate multilevel samples. The estimator emerges as a useful alternative or complement to maximum likelihood because it often outperforms maximum likelihood in small to moderate multilevel samples in terms of convergence, bias, error variance, and power. The proposed estimator is implemented as a function in R using lavaan and is illustrated using a multilevel mediation example.

Evaluation of an Alternative Estimator of Learning Curve Lot Midpoints

1994 ◽  
Vol 11 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Daniel A. Nussbaum
Keyword(s):  
Learning Curve ◽  
Alternative Estimator

An Input–Process–Output Model of Pilot Core Competencies

2017 ◽  
Vol 7 (2) ◽  
pp. 78-85 ◽  
Author(s):  
Heikki Mansikka ◽  
Don Harris ◽  
Kai Virtanen
Keyword(s):  
Path Analysis ◽  
Team Performance ◽  
Core Competencies ◽  
Core Competency ◽  
Principal Component ◽  
Analysis Model ◽  
Input Process ◽  
The Core ◽  
Performance Framework ◽  
Process Output

Abstract. The aim of this study was to investigate the relationship between the flight-related core competencies for professional airline pilots and to structuralize them as components in a team performance framework. To achieve this, the core competency scores from a total of 2,560 OPC (Operator Proficiency Check) missions were analyzed. A principal component analysis (PCA) of pilots’ performance scores across the different competencies was conducted. Four principal components were extracted and a path analysis model was constructed on the basis of these factors. The path analysis utilizing the core competencies extracted adopted an input–process–output’ (IPO) model of team performance related directly to the activities on the flight deck. The results of the PCA and the path analysis strongly supported the proposed IPO model.

A comparison of path analysis and factor analysis for some simulated behavioral data

1976 ◽  
Author(s):  
Benjamin Fruchter ◽  
Philippe Lasserre
Keyword(s):  
Factor Analysis ◽  
Path Analysis ◽  
Behavioral Data

Pengaruh Good Corporate Governance Terhadap Nilai Perusahaan Dengan Variabel Intervening Profitabilitas

2017 ◽  
Vol 25 (1) ◽  
pp. 13-39
Author(s):  
Achmad Tjahjono ◽  
Siti Chaeriyah
Keyword(s):  
Corporate Governance ◽  
Path Analysis ◽  
Executive Director ◽  
Audit Committee ◽  
Positive Impact ◽  
Institutional Ownership ◽  
Analysis Tool ◽  
Manufacturing Companies ◽  
Company Value ◽  
Good Corporate Governance

The Company was founded with the goal of increasing the value of the company as well as to provide prosperity for the owners or shareholders. Good Corporate Governance and profitability is an effort to enhance company value. This study aims to determine the influence of good corporate governance to company value with profitability as intervening variable. The population of this research is manufacturing companies listed in Indonesia Stock Exchange in 2010 - 2014. The sample is taken by using purposive sampling method. Under this method, as many as 123 companies were obtained. The analysis tool to test the hypothesis is path analysis with AMOS software version 21. Data analysis method is descriptive analysis, path analysis, and sobeltest. The results of this study indicate that managerial ownership, the audit committee and the profitability have positive impact toward the of the company value, institutional ownership has positive impact but not significant, non-executive director with negative effect tendency on the company value. The results of this study also showed that profitability cannot mediate the effect of good corporate governance mechanisms on company value. It can be suggested to replace the intervening variable with other variables such as quality of earnings instead of profitability since it is declined as an intervening variable. non-executive director and institutional ownership does not contribute any positive and significant effect on company value and profitability. The following research can use another proxy in the measurement process and consider other theories that could explain comprehensively.

PENGARUH KELENTUKAN, KEKUATAN OTOT TUNGKAI DAN KOORDINASI MATA-KAKI TERHADAP KETERAMPILAN SEPAKSILA PADA ATLET SEPAKTAKRAW SULAWESI SELATAN

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
SUHARTIWI SUHARTIWI
Keyword(s):  
Path Analysis

Salah satu faktor terpenting dalam pencapaian prestasi maksimal pada atlet sepaktakraw adalah dengan memiliki kondisi fisik yang dapat menunjang keterampilan khususnya keterampilan sepaksila dalam permainan sepaktakraw. Kelentukan yang baik dapat memudahkan atlet dalam meluweskan lipatan salah satu kaki ke atas saat melakukan keterampilan sepaksila, dibutuhkan kekuatan otot tungkai pada saat salah satu kaki yang menjadi tumpuan berat badan dan koordinasi mata kaki sangat dibutuhkan sebelum sesaat melakukan sepakan dalam permainan sepaksila.Jenis penelitian ini ialah penelitian deskriptif dengan menggunakan teknik analisis jalur (Path Analysis). Populasinya adalah atlet sepaktakraw Sulawesi Selatan yang termasuk dalam pembinaan Sulsel Maju II dan PPLP ( Pusat Pendidikan Latihan Pelajar) yang totalnya berjumlah 24 orang. Teknik penentuan sampelnya adalah sampel jenuh. Teknik anaslisa data yang digunakan adalah analisis statistik deskriptif dan analisis jalur dengan bantuan program computer SPSS 16.Hasil penelitian ini menunjukkan bahwa (1) Atlet sepaktakraw Sulawesi Selatan memiliki kelentukan berpengaruh secara langsung terhadap koordinasi mata kaki sebesar 42,90%.(2) Kekuatan otot tungkai berpengaruh langsung terhadap koordinasi mata kaki sebesar 9,61%. (3) Kelentukan berpengaruh secara langsung dan tidak langsung terhadap keterampilan sepaksila pada permainan sepaktakraw sebesar 20,64%. (4) Kekuatan otot tungkai berpengaruh secara langsung dan tidak langsung terhadap keterampilan sepaksila pada permainan sepaktakraw sebesar 12,27%. (5) Koordinasi mata kaki berpengaruh secara langsung terhadap keterampilan sepaksila pada permainan sepaktakraw sebesar 15,44%.Kata Kunci : Kelentukan, Kekuatan otot tungkai, koordinasi mata kaki, keterampilan sepaksila.

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