Testing Categorized Bivariate Normality With Two-Stage Polychoric Correlation Estimates

Methodology ◽  
2009 ◽  
Vol 5 (4) ◽  
pp. 131-136 ◽  
Author(s):  
Alberto Maydeu-Olivares ◽  
Carlos García-Forero ◽  
David Gallardo-Pujol ◽  
Jordi Renom
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Polychoric Correlation ◽  
Two Stage ◽  
Chi Square ◽  
Polychoric Correlations ◽  
Asymptotically Efficient ◽  
Two Stages ◽  
Bivariate Normality

Structural equation modeling (SEM) with ordinal indicators rely on an assumption of categorized normality. This assumption may be tested for pairs of variables using the likelihood ratio G2 or Pearson’s X2 statistics. For increased computational efficiency, SEM programs usually estimate polychoric correlations in two stages. However, two-stage polychoric estimates are not asymptotically efficient and G2 and X2 need not be asymptotically chi-square when the estimator is not efficient. Recently, Maydeu-Olivares and Joe (2005) have introduced a new statistic, Mn , that is asymptotically chi-square even for estimators that are not efficient. We investigate the behavior of G2, X2, and Mn when testing underlying bivariate normality with polychoric correlations estimated in two stages.

Impulsivity and Aggression: A Meta-analysis Using the UPPS Model of Impulsivity

2019 ◽  
Author(s):  
Konrad Bresin
Keyword(s):  
Structural Equation Modeling ◽  
Sensation Seeking ◽  
Structural Equation ◽  
Meta Analysis ◽  
The Other ◽  
Equation Modeling ◽  
Negative Urgency ◽  
Two Stage ◽  
Trait Impulsivity

Trait impulsivity has long been proposed to play a role in aggression, but the results across studies have been mixed. One possible explanation for the mixed results is that impulsivity is a multifaceted construct and some, but not all, facets are related to aggression. The goal of the current meta-analysis was to determine the relation between the different facets of impulsivity (i.e., negative urgency, positive urgency, lack of premeditation, lack of perseverance, and sensation seeking) and aggression. The results from 93 papers with 105 unique samples (N = 36, 215) showed significant and small-to-medium correlations between each facet of impulsivity and aggression across several different forms of aggression, with more impulsivity being associated with more aggression. Moreover, negative urgency (r = .24, 95% [.18, .29]), positive urgency (r = .34, 95% [.19, .44]), and lack of premeditation (r = .23, 95% [.20, .26]) had significantly stronger associations with aggression than the other scales (rs < .18). Two-stage meta-analytic structural equation modeling showed that these effects were not due to overlap among facets of impulsivity. These results help advance the field of aggression research by clarifying the role of impulsivity and may be of interest to researchers and practitioners in several disciplines.

scholarly journals KONTRIBUSI RANTAI NILAI TERHADAP PENINGKATAN DAYA SAING PERIKANAN TUNA DI KABUPATEN CILACAP DAN SEKITARNYA

2018 ◽  
Vol 10 (1) ◽  
pp. 11
Author(s):  
Bambang Nariyono ◽  
Arief Daryanto ◽  
M Firdaus ◽  
Setijadi Johar
Keyword(s):  
Structural Equation Modeling ◽  
Value Chain ◽  
Structural Equation ◽  
Global Market ◽  
Second Order ◽  
Equation Modeling ◽  
P Value ◽  
Chi Square ◽  
Tuna Industry ◽  
Tuna Fishery

Indonesia dalam industri tuna sangat diperhitungkan karena posisinya sebagai pemasok lebih dari 15 % produksi tuna dunia, tetapi di sisi lain daya saing perikanan tuna masih rendah. Tujuan dari penelitian ini adalah menganalisis kontribusi rantai nilai perikanan tuna terhadap daya saing industri perikanan tuna di Kabupaten Cilacap. Penelitian dilaksanakan pasa bulan April sampai dengan September 2017. Hasil analisis Second Order Structural Equation Modeling didapatkan bahwa rantai nilai berpengaruh terhadap daya saing industri tuna dengan loading factor 0.540 dan nilai p yang signifikan. Pengujian terhadap model secara simultan terbukti bahwa model telah fit dengan telah dipenuhinya semua ukuran fitting model yang diindikasikan dengan nilai Chi-Square kecil yaitu 301.252, RMSEA = 0.072, GFI = 0.907, CFI= 0.923, dan CMIN/DF = 1.814. Temuan penelitian ini membuktikan bahwa rantai nilai mempunyai pengaruh yang signifikan terhadap daya saing industri tuna. Dengan demikian strategi yang tepat untuk memperkuat daya saing industri tuna dapat dilakukan dengan cara meningkatkan rantai nilai perikanan tuna terutama dari aspek operasional, outbond logistic, dan services.Indonesia is the world’s larget tuna produser with contributing 15 percent to the world tuna market. However, the competitiveness of tuna fishery is still low. The aim of this research is to analyze the contribution of value chain of tuna fishery toward competitiveness of tuna industry in Cilacap. The study was conducted from April to September 2017. The results of analysis using using second order Structural Equation Modeling method (SEM) found that the value chain influenced the competitiveness of tuna industry with loading factor of 0.540 and significant p value. Tests on the model simultaneously proved that the model has been fit with the fulfillment of all fittings of the model. It gives indication with variables value, such as : Value of Chi-square is low with value 301.252; 0.072 for Root Mean Square Error of Approximation (RMSEA); 0.907 for Goodness Fit Index (GFI); 0.907 for (CFI); and 1.814 for minimum discrepancy (CMIN/DF). This research gives evidence that value chain has a significant impact toward competitiveness of tuna fishery industries.The best strategies to increase competitiveness of tuna fishery industries is increasing a value chain of of tuna fishery industries, Mainly from operational aspect, outbond logistic and services to raise tuna commodity productvity in global market.

scholarly journals PENGARUH KOMPETENSI GURU TERHADAP KOMITMEN PROFESIONAL DAN DAMPAKNYA PADA KINERJA SERTA KEPUASAN KERJA GURU MATEMATIKA SMP DAN MTS

2014 ◽  
Vol 1 (2) ◽  
pp. 285
Author(s):  
Zuhdy Tafqihan ◽  
Suryanto Suryanto
Keyword(s):  
Structural Equation Modeling ◽  
Random Sampling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Two Stage ◽  
Cluster Random Sampling

Penelitian ini bertujuan untuk memperoleh model hubungan kausalitas dari variabel-variabel kompetensi, komitmen profesional, kinerja dan kepuasan kerja guru matematika. Populasi dalam penelitian ini adalah seluruh guru matematika SMP dan MTs di Kabupaten Ponorogo yang berjumlah 262 orang. Sampel sejumlah 82 orang ditentukan melalui teknik two stage cluster random sampling. Instrumen penelitian ini adalah kuesioner dan lembar penilaian/observasi. Kuesioner digunakan untuk mengumpulkan data komitmen profesional dan kepuasan kerja guru matematika, sedangkan lembar penilaian/observasi digunakan untuk mengumpulkan data kompetensi dan kinerja guru matematika. Data yang diperoleh dianalisis dengan metode Structural Equation Modeling (SEM).Hasil penelitian menunjukkan bahwa: (1) terdapat pengaruh positif kompetensi terhadap komitmen profesional sebesar 15,9%; (2) terdapat pengaruh positif kompetensi terhadap kinerja sebesar 63,6%; (3) terdapat pengaruh positif komitmen profesional terhadap kinerja sebesar 15,9%; dan (4) terdapat pengaruh positif komitmen profesional terhadap kepuasan kerja sebesar 37,8%. Hasil-hasil penelitian di atas dapat mengkonfirmasi kesimpulan penelitian-penelitian sebelumnya. Kata kunci: kompetensi guru, komitmen profesional, kinerja, kepuasan kerja, Structural Equation Modeling (SEM)

scholarly journals ANALISIS FAKTOR FAKTOR YANG MEMPENGARUHI MINAT WIRAUSAHA DIKALANGAN INDUSTRI KECIL DI KABUPATEN TOJO UNA UNA

2018 ◽  
Vol 3 (1) ◽  
pp. 21
Author(s):  
Rahmaniah Malik ◽  
Nadzirah Ikasari ◽  
Fardina Ekawaty Napu
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Equation Modeling ◽  
Chi Square

Keberadaan perusahaan industri baru berimplikasi pada terciptanya lapangan pekerjaan yang membuka kesempatan kepada para pencari kerja. Perusahaan industri di Kabupaten Tojo Una-Una dapat dikelompokkan dalam beberapa kategori menurut banyaknya tenaga kerja yang digunakan yaitu : industri kerajinan rumah tangga jumlah tenaga kerja 1 s/d 4 orang, industri kecil dengan jumlah tenaga kerja 5 s/d 9 orang, industri sedang dengan jumlah tenaga kerjanya 20 s/d 100 orang, dan industri besar dengan jumlah tenaga kerja lebih dari 100 orang. Dalam menganalisis data yang telah dikumpulkan berupa observasi, wawancara, dan kuesioner. Data kemudian dianalisis dengan menggunakan metode SEM (Structural Equation Modeling) atau model persamaan terstruktur. Data hasil pengamatan dalam penyusunan tugas akhir ini berdistribusi normal, sebagaimana yang disyaratkan dalam metode SEM. Selain data yang berdistribusi normal data dalam pengamatan ini tidak ditemukannya outliers dan juga Multikolinieritas. Setelah syarat-syarat dalam metode SEM terpenuhi langkah selanjutnya yaitu mengistimasi model yang telah dibuat. Nilai uji Goodness of fit yang diperoleh Chi Square = 237,997; Probabilitas = 0,000; RMR = 0,044; GFI = 0,817; AGFI = 0,765; TLI = 0,642; CFI = 0,691; NFI = 0,446; RMSEA = 0,068. Dalam uji hipotesis variabel toleransi akan resiko tidak berpengaruh signifikan terhadap variabel motivasi wirausaha. Akan tetapi, variabel keberhasilan diri dan variabel kebebasan dalam bekerja berpengaruh signifikan terhadap variabel motivasi wirausaha.

Modeling the Effect of Multidimensional Trust on Individual Monetary Donations to Charitable Organizations

2018 ◽  
Vol 47 (3) ◽  
pp. 623-644 ◽  
Author(s):  
Ibrahim S. Alhidari ◽  
Tania M. Veludo-de-Oliveira ◽  
Shumaila Y. Yousafzai ◽  
Mirella Yani-de-Soriano
Keyword(s):  
Saudi Arabia ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Charitable Organizations ◽  
Two Stage ◽  
Second Stage ◽  
Stage 4 ◽  
Donation Behavior ◽  
Modeling Data

This study develops and validates a model that evaluates the effect of trust on individual monetary donations to charitable organizations (COs). Data were collected in Saudi Arabia using a two-stage approach and were analyzed via structural equation modeling. Data on psychosocial variables were collected in the first stage, and data on behavior were collected in the second stage, 4 weeks later. The findings confirm the study’s novel multidimensional perspective of trust in the context of individual monetary donations to COs in Saudi Arabia. The results validate the view that trust is present only when the individuals concerned are disposed to trust others and when they believe that the COs can conduct their charitable mission, are honest in the use of their donations, and prioritize beneficiaries’ rights. Individuals’ trust in COs affects both the intention to donate and future monetary donation behavior.

scholarly journals We need to change how we compute RMSEA for nested model comparisons in structural equation modeling

2021 ◽  
Author(s):  
Victoria Savalei ◽  
Jordan Brace ◽  
Rachel T. Fouladi
Keyword(s):  
Structural Equation Modeling ◽  
Measurement Invariance ◽  
Structural Equation ◽  
Model Comparison ◽  
Equation Modeling ◽  
Future Research ◽  
Chi Square ◽  
Nested Model ◽  
Nested Models ◽  
Difference Test

Comparison of nested models is common in applications of structural equation modeling (SEM). When two models are nested, model comparison can be done via a chi-square difference test or by comparing indices of approximate fit. The advantage of fit indices is that they permit some amount of misspecification in the additional constraints imposed on the model, which is a more realistic scenario. The most popular index of approximate fit is the root mean square error of approximation (RMSEA). In this article, we argue that the dominant way of comparing RMSEA values for two nested models, which is simply taking their difference, is problematic and will often mask misfit. We instead advocate computing the RMSEA associated with the chi-square difference test. We are not the first to propose this idea, and we review numerous methodological articles that have suggested it. Nonetheless, these articles appear to have had little impact on actual practice. The modification of current practice that we call for may be particularly needed in the context of measurement invariance assessment. We illustrate the difference between the current approach and our advocated approach on three examples, where two involve multiple-group and longitudinal measurement invariance assessment and the third involves comparisons of models with different numbers of factors. We conclude with a discussion of limitations and future research directions.

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