Introduction to Structural Equation Modelling Using SPSS and Amos

By N. Blunch. 2008

668 citations recorded by the source corpus.

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Citations in the corpus

Does Tourism Growth Influence Economic Development? (2015, background): “Although one software for estimation of SEM models provided TCD (total coefficient of determination) as the statistic of goodness of fit, EQS does not provide this statistic, despite which the goodness of fit of the model can be assessed by the various statistics presented in Table 4.”
Do homes that are more energy efficient consume less energy?: A structural equation model for England's residential sector (2011, methodology): “For detailed mathematical derivation of SEM see the following textbooks (Kaplan 2009; Blunch 2008; Kline 2005; Tabachnick 2007) Structural equation models allow both confirmatory and exploratory modelling, meaning that such models can be used for both theory testing and theory development.”
Destination image, on-site experience and behavioural intentions: path analytic validation of a marketing model on domestic tourists (2017, methodology): “90 for the CFI and GFI (Blunch, 2008; Kline, 2011); values less than 0.08 for RMSEA (Hair et al., 2014); while for the PNFI, Mulaik et al. (1989) suggest that it is common to obtain values within the 0.”
Assessing Resilience Across Cultures Using Mixed Methods: Construction of the Child and Youth Resilience Measure (2011, methodology): “…solution allows for the maximization of the sum of square factor loadings, where the first component accounts for the largest share of the total variance in the data, yielding those items of the measure that perform best for the sample in question (Blunch, 2008; Pett, Lackey, & Sullivan, 2003).”
A cross-cultural study of the intention to use mobile banking between Lebanese and British consumers: Extending UTAUT2 with security, privacy and trust (2019, background): “Moreover, SEM's ability to determine the construct validity of the proposed model's variables was remarked in the context of social science research, most likely contributing to its wide acceptance in this ﬁ eld as well as that of IS and behavioural science [109,112].”
The consumer’s perception of artificial food additives: Influences on acceptance, risk and benefit perceptions (2014, methodology): “Differences in the model for the two versions of the questionnaire were tested via multi-group analysis, as described in the relevant literature (Blunch, 2008; Byrne, 2001).”
Core self-evaluation and life satisfaction: The person-environment fit perspective (2015, methodology): “Smaller values of AIC and ECVI indicate a better model fit (Blunch, 2008).”
Testing an integrated destination image model across residents and tourists (2017, background): “The constrained model demonstrated a good fit: c2(41) ¼ 98.8, p 0.001, CMIN/ DF ¼ 2.41, GFI ¼ 0.95, CFI ¼ 0.95, RMSEA ¼ 0.057.”
The Developmental Relationship Between Language and Low Early Numeracy Skills Throughout Kindergarten (2014, methodology): “In this study, goodness of fit was evalu ated with three indicators recommended by Blunch (2008): chisquare (χ2) with its p value, comparative fit index, and root mean square error of approximation with its p close value.”
Edinburgh Handedness Inventory – Short Form: A revised version based on confirmatory factor analysis (2014, background): “Some authors have suggested 5-point response scales be treated as ordinal (Kline, 2011), while others have suggested treatments as continuous (Blunch, 2008).”
A unitary executive function predicts intelligence in children (2012, methodology): “10 (Blunch, 2008). Significance of correlation and path coefficients was determined in the same manner as Friedman et al. (2006). That is, χ(2) difference tests were conducted when removing an individual regression parameter.”
Resourcing new businesses: social networks, bootstrapping and firm performance (2010, background): “Although standards for such indexes are not fully established, a value of 0.90 or higher for the CFI and TLI and a value of 0.08 or lower for the RMSEA are typically suggested as indicating adequate fit (Blunch 2008).”
Relationships between organizational justice, organizational trust and organizational commitment: a cross-cultural study of China, South Korea and Australia (2017, methodology): “Following standard preparatory procedures (Hair, Black, Babin, & Anderson, 2010), discriminant and convergent validity was examined using confirmatory factor analysis (CFA) (AMOS 20, maximum likelihood) to determine whether the four factors were distinct from each other.”
Teachers’ Engagement at Work: An International Validation Study (2012, methodology): “We included three measures of goodness-of-fit: χ2/df ratio, wherein a ratio < 3.0 indicates a good fit; CFI, where > .90 indicates a good fit, and root mean square error of approximation (RMSEA), where < .09 or < .10 suggests a well-fitting model (e.g., Arbuckle, 2007; Blunch, 2008; Byrne, 2004).”