An approximate measurement invariance approach to within-couple relationship quality

This study aimed at demonstrating the usefulness and flexibility of the Bayesian structural equation modeling approximate measurement invariance (BSEM-AMI) approach to within-couple data. The substantive aim of the study was investigating partner differences in the perception of relationship quality (RQ) in a sample of intact couples (n = 435) drawn from the first sweep of the Millenium Cohort Study. Configural, weak and strong invariance models were tested using both maximum likelihood (ML) and BSEM approaches. As evidence of a lack of strong invariance was found, full and partial AMI models were specified, allowing nine different prior variances or “wiggle rooms.” Although we could find an adequately fitting BSEM-AMI model allowing for approximate invariance of all the intercepts, the two-step approach proposed by Muthén and Asparouhov (2013b) for identifying problematic parameters and applying AMI only to them provided less biased results. Findings similar to the ML partial invariance model, led us to conclude that women reported a higher RQ than men. The results of this study highlight the need to inspect parameterization indeterminacy (or alignment) and support the efficacy of the two-step approach to BSEM-AMI.

[1]  Alyson F. Shapiro,et al.  The baby and the marriage: identifying factors that buffer against decline in marital satisfaction after the first baby arrives. , 2000, Journal of family psychology : JFP : journal of the Division of Family Psychology of the American Psychological Association.

[2]  John H. Grych,et al.  Interparental Conflict and Child Development: Foundations , 2001 .

[3]  G. Spanier.  Measuring Dyadic Adjustment: new scales for assessing the quality of marriage and similar dyads , 1976 .

[4]  Bengt Muthén,et al.  Bayesian structural equation modeling: a more flexible representation of substantive theory. , 2012, Psychological methods.

[5]  M. Crowe,et al.  The Golombok Rust Inventory of Marital State (GRIMS) , 2010 .

[6]  B. Byrne,et al.  Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. , 1989 .

[7]  T. Raykov.  Estimation of Composite Reliability for Congeneric Measures , 1997 .

[8]  Jeffrey B. Jackson,et al.  Gender Differences in Marital Satisfaction: A Meta-analysis , 2014 .

[9]  L. Leslie,et al.  The Future of Marriage , 2000 .

[10]  Guangjian Zhang,et al.  Predicting marital satisfaction from self, partner, and couple characteristics: is it me, you, or us? , 2008, Journal of personality.

[11]  R. Slatcher,et al.  Marital quality and health: a meta-analytic review. , 2014, Psychological bulletin.

[12]  L. Malmberg,et al.  The Comparison and Interdependence of Maternal and Paternal Influences on Young Children's Behavior and Resilience , 2011, Journal of clinical child and adolescent psychology : the official journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53.

[13]  Mahima Singh.  The Checklist , 2016 .

[14]  Albert Satorra,et al.  A scaled difference chi-square test statistic for moment structure analysis , 1999 .

[15]  T. Brown,et al.  Confirmatory Factor Analysis for Applied Research , 2006 .

[16]  P. D. Silva.  The Golombok Rust inventory of sexual satisfaction : J. Rust and S. Golombok: NFER—Nelson, Windsor (1986). Pages vi + 26. £17.95 , 1987 .

[17]  M. Crowe,et al.  The GRIMS. A psychometric instrument for the assessment of marital discord , 1990 .

[18]  K. Shadan,et al.  Available online: , 2012 .

[19]  H. Locke,et al.  SHORT MARITAL ADJUSTMENT AND PREDICTION TESTS: THEIR RELIABILITY AND VALIDITY , 1959 .

[20]  D. A. Kenny,et al.  Models of Non-Independence in Dyadic Research , 1996 .

[21]  Frank D. Fincham,et al.  Marital Conflict , 2003 .

[22]  Clark Christensen,et al.  A REVISION OF THE DYADIC ADJUSTMENT SCALE FOR USE WITH DISTRESSED AND NONDISTRESSED COUPLES: CONSTRUCT HIERARCHY AND MULTIDIMENSIONAL SCALES , 1995 .

[23]  N. Hjort,et al.  Post-Processing Posterior Predictive p Values , 2006 .

[24]  Phil Wood.  Confirmatory Factor Analysis for Applied Research , 2008 .

[25]  F. Fincham,et al.  Research on the Nature and Determinants of Marital Satisfaction: A Decade in Review , 2000 .

[26]  D. A. Kenny,et al.  Partner effects in relationship research: Conceptual issues, analytic difficulties, and illustrations , 1999 .

[27]  Bengt Muthén,et al.  Simultaneous factor analysis of dichotomous variables in several groups , 1981 .

[28]  Bengt Muthén,et al.  Bayesian SEM : A more flexible representation of substantive theory , 2010 .

[29]  J. Hox,et al.  A checklist for testing measurement invariance , 2012 .

[30]  Lars Tummers,et al.  Facing off with Scylla and Charybdis: a comparison of scalar, partial, and the novel possibility of approximate measurement invariance , 2013, Front. Psychol..

[31]  J. A. Walsh,et al.  Invariance and convergent and discriminant validity between mothers' and fathers' ratings of oppositional defiant disorder toward adults, ADHD-HI, ADHD-IN, and academic competence factors within Brazilian, Thai, and American children. , 2008, Psychological assessment.

[32]  B. Muthén,et al.  How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power , 2002 .

[33]  Tihomir Asparouhov,et al.  Item Response Modeling in Mplus: A Multi-Dimensional, Multi-Level, and Multi-Timepoint Example , 2013 .

[34]  Gordon W. Cheung,et al.  Assessing Extreme and Acquiescence Response Sets in Cross-Cultural Research Using Structural Equations Modeling , 2000 .

[35]  J. Rust,et al.  The Golombok-Rust Inventory of Sexual Satisfaction (GRISS). , 1985, The British journal of clinical psychology.

[36]  W. Meredith.  Measurement invariance, factor analysis and factorial invariance , 1993 .

[37]  Erica Frank,et al.  The Second Shift , 2002 .

[38]  R. Krueger,et al.  Factorial invariance of the Dyadic Adjustment Scale across gender. , 2009, Psychological assessment.

[39]  F. Chen.  Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance , 2007 .

[40]  H. Marsh,et al.  In Search of Golden Rules: Comment on Hypothesis-Testing Approaches to Setting Cutoff Values for Fit Indexes and Dangers in Overgeneralizing Hu and Bentler's (1999) Findings , 2004 .