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  • Practical guide of the integrated structural equation modeling (SEM) with LISREL & AMOS for marketing and social sciences thesis

    Practical guide of the integrated structural equation modeling (SEM) with LISREL & AMOS for marketing and social sciences thesis

    • Mochammad Riyadh Rizki Adam
    • Deepublish
    • 2018
    • 978-602-475-219-4
    Sinopsis

    Hair et al. (2007) explains that Structural Equation Modeling (SEM) is“a family of statistical models (multivariate technique) that seek to explain the relationships among multiple variables. It examines the structure of interrelationships expressed in a series of equations, similar to a series of multiple regression equations.” Structural equation modeling would be very good for the researchers who face a set of interrelated questions in their study. For example, what factors influence a brand trust? How does that brand trust combine with other factors would affect brand loyalty? If you face this situation in management, you need a multivariate technique to answer that issues. And, you will get the multivariate data as the results

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Kode Buku : 213439
Kode Klasifikasi : 004
Judul Buku : Practical guide of the integrated structural equation modeling (SEM) with LISREL & AMOS for marketing and social sciences thesis
Edisi : 1
Penulis : Mochammad Riyadh Rizki Adam
Penerbit : Deepublish
Bahasa : Inggris
Tahun : 2018
ISBN : 978-602-475-219-4
Tajuk Subjek : Struktur Data
Deskripsi : x, 171 hlm.: ill.; 29 cm
Eksemplar : 3
Stok : 3
Petugas : Rizki Arsika Yunita, S.Hum
Hair et al. (2007) explains that Structural Equation Modeling (SEM) is“a family of statistical models (multivariate technique) that seek to explain the relationships among multiple variables. It examines the structure of interrelationships expressed in a series of equations, similar to a series of multiple regression equations.”
Structural equation modeling would be very good for the researchers who face a set of interrelated questions in their study. For example, what factors influence a brand trust? How does that brand trust combine with other factors would affect brand loyalty? If you face this situation in management, you need a multivariate technique to answer that issues. And, you will get the multivariate data as the results
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