Representative Sampling of the Via Assessment Suite for Adults

References

• Allport, G. W. (1961). Pattern and growth in personality. Rinehart & Winston.
   Google Scholar
• Asparouhov, T., Muthén, B., & Morin, A. J. S. (2015). Bayesian structural equation modeling with cross-loadings and residual covariances: Comments on Stromeyer et al. Journal of Management, 41(6), 1561–1577. https://doi.org/10.1177/0149206315591075
   Web of Science ®Google Scholar
• Ardelt, M. (2010). Are older adults wiser than college students? A comparison of two age cohorts. Journal of Adult Development, 17(4), 193–207. https://doi.org/10.1007/s10804-009-9088-5
   Web of Science ®Google Scholar
• Auerswald, M., & Moshagen, M. (2019). How to determine the number of factors to retain in exploratory factor analysis: A comparison of extraction methods under realistic conditions. Psychological Methods, 24(4), 468–491. https://doi.org/10.1037/met0000200
   PubMed Web of Science ®Google Scholar
• Baltes, P. B., & Staudinger, U. M. (2000). Wisdom: A metaheuristic (pragmatic) to orchestrate mind and virtue toward excellence. American Psychologist, 55(1), 122–136. https://doi.org/10.1037/0003-066X.55.1.122
   PubMed Web of Science ®Google Scholar
• Blanchard, T., McGrath, R. E. & Jayawickreme, E. (in press). Resilience in the face of interpersonal loss: The role of character strengths. Applied Psychology: Health and Well-Being. https://doi.org/10.1111/aphw.12273
   Google Scholar
• Braeken, J., & van Assen, M. A. L. M. (2017). An empirical Kaiser criterion. Psychological Methods, 22(3), 450–466. https://doi.org/10.1037/met0000074
   PubMed Web of Science ®Google Scholar
• Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14(3), 464–504. https://doi.org/10.1080/10705510701301834
   Web of Science ®Google Scholar
• Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902_5
   Web of Science ®Google Scholar
• Cooley, S. J., Quinton, M. L., Holland, M. J. G., Parry, B. J., & Cumming, J. (2019). The experiences of homeless youth when using strengths profiling to identify their character strengths. Frontiers in Psychology, 10, 2036. https://doi.org/10.3389/fpsyg.2019.02036
   PubMed Web of Science ®Google Scholar
• Dahlsgaard, K., Peterson, C., & Seligman, M. E. P. (2005). Shared virtue: The convergence of valued human strengths across culture and history. Review of General Psychology, 9(3), 203–213. https://doi.org/10.1037/1089-2680.9.3.203
   Web of Science ®Google Scholar
• Epskamp, S., Rhemtulla, M. T., & Borsboom, D. (2017). Generalized network psychometrics: Combining network and latent variable models. Psychometrika, 82(4), 904–927. https://doi.org/10.1007/s11336-017-9557-x
   PubMed Web of Science ®Google Scholar
• Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). Sage.
   Google Scholar
• Floyd, F. J., & Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7(3), 286–299. https://doi.org/10.1037/1040-3590.7.3.286
   Web of Science ®Google Scholar
• Graham, C., & Pinto, S. (2019). Unequal hopes and lives in the USA: Optimism, race, place, and premature mortality. Journal of Population Economics, 32(2), 665–733. https://doi.org/10.1007/s00148-018-0687-y
   Web of Science ®Google Scholar
• Gray-Little, B., & Hafdahl, A. R. (2000). Factors influencing racial comparisons of self-esteem: A quantitative review. Psychological Bulletin, 126(1), 26–54. https://doi.org/10.1037/0033-2909.126.1.26
   PubMed Web of Science ®Google Scholar
• Green, S. B., & Yang, Y. (2009). Commentary on coefficient alpha: A cautionary tale. Psychometrika, 74(1), 121–135. https://doi.org/10.1007/s11336-008-9098-4
   Web of Science ®Google Scholar
• Han, H. (2020). Implementation of Bayesian multiple comparison correction in the second-level analysis of fMRI data: With pilot analyses of simulation and real fMRI datasets based on voxelwise inference. Cognitive Neuroscience, 11(3), 157–169. https://doi.org/10.1080/17588928.2019.1700222
   PubMed Web of Science ®Google Scholar
• Han, H. (2021). A method to adjust a prior distribution in Bayesian second-level fMRI analysis. PeerJ, 9(9), e10861. https://doi.org/10.7717/peerj.10861
   PubMed Web of Science ®Google Scholar
• Han, H., & McGrath, R. E. (2021). Latent structural analysis for measures of character strengths: Achieving adequate fit. Manuscript submitted for publication.
   Google Scholar
• Heo, J., Jeon, S. Y., Oh, C. M., Hwang, J., Oh, J., & Cho, Y. (2017). The unrealized potential: Cohort effects and age-period-cohort analysis. Epidemiol Health, 39, e2017056. https://doi.org/10.4178/epih.e2017056
   PubMed Web of Science ®Google Scholar
• Jones, M. S., House, L. A., & Gao, Z. (2015). Respondent screening and revealed preference axioms: Testing quarantining methods for enhanced data quality in web panel surveys. Public Opinion Quarterly, 79(3), 687–709. https://doi.org/10.1093/poq/nfv015
   Web of Science ®Google Scholar
• Kincaid, J. P., Fishburne, R. P., Rogers, R. L., & Chissom, B. S. (1975). Derivation of new readability formulas (automated readability index, fog count, and Flesch reading ease formula) for Navy enlisted personnel (Research Branch Report 8-75). Memphis, TN: Chief of Naval Technical Training, Naval Air Station.
   Google Scholar
• Li, Y., Li, Y., Duan, W., Guan, Q., & Tao, Y. (in press). Testing the contribution of general factor of character strengths to well-being: An exploratory bifactor approach. Current Psychology: A Journal for Diverse Perspectives on Diverse Psychological Issues. https://doi.org/10.1007/s12144-020-01223-z
   Google Scholar
• Lindwall, M., Barkoukis, V., Grano, C., Lucidi, F., Raudsepp, L., Liukkonen, J., & Thøgersen-Ntoumani, C. (2012). Method effects: The problem with negatively versus positively keyed items. Journal of Personality Assessment, 94(2), 196–204. https://doi.org/10.1080/00223891.2011.645936
   PubMed Web of Science ®Google Scholar
• Linley, P. A., Maltby, J., Wood, A. M., Joseph, S., Harrington, S., Peterson, C., Park, N., & Seligman, M. E. P. (2007). Character strengths in the United Kingdom: The VIA inventory of strengths. Personality and Individual Differences, 43(2), 341–351. https://doi.org/10.1016/j.paid.2006.12.004
   Web of Science ®Google Scholar
• Lomas, T. (2021). The dimensions of prosociality: A cross-cultural lexical analysis. Current Psychology, 40(3), 1336–1347. https://doi.org/10.1007/s12144-018-0067-5
   Web of Science ®Google Scholar
• Lorenzo-Seva, U., Timmerman, M. E., & Kiers, H. A. L. (2011). The Hull method for selecting the number of common factors. Multivariate Behavioral Research, 46(2), 340–364. https://doi.org/10.1080/00273171.2011.564527
   PubMed Web of Science ®Google Scholar
• McGrath, R. E. (2014). Scale- and item-level factor analyses of the VIA inventory of strengths. Assessment, 21(1), 4–14. https://doi.org/10.1177/1073191112450612
   PubMed Web of Science ®Google Scholar
• McGrath, R. E. (2015). Integrating psychological and cultural perspectives on virtue: The hierarchical structure of character strengths. The Journal of Positive Psychology, 10(5), 407–424. https://doi.org/10.1080/17439760.2014.994222
   Web of Science ®Google Scholar
• McGrath, R. E. (2019). Technical report: The VIA Assessment Suite for Adults: Development and initial evaluation (Rev. ed.). VIA Institute on Character. https://evada-assets.global.ssl.fastly.net/76d1ea39-a4eb-4270-b9dc-899653415f8f/assets/Technical%20Report%20Revised%20Edition%202019_1.pdf
   Google Scholar
• McGrath, R. E. (in press). Darwin meets Aristotle: Fundamental virtues as contributors to addressing current cultural tensions. Journal of Positive Psychology. https://doi.org/10.1080/17439760.2020.1752781
   Web of Science ®Google Scholar
• McGrath, R. E., & Brown, M. (2020). Using the VIA classification to advance a psychological science of virtue. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.565953
   PubMed Web of Science ®Google Scholar
• McGrath, R. E., Greenberg, M. J., & Hall-Simmonds, A. (2018). Scarecrow, Tin Woodsman, and Cowardly Lion: The three-factor model of virtue. The Journal of Positive Psychology, 13(4), 373–392. https://doi.org/10.1080/17439760.2017.1326518
   Web of Science ®Google Scholar
• McGrath, R. E., Hall-Simmonds, A., & Goldberg, L. R. (2020). Are measures of character and personality distinct? Evidence from observed-score and true-score analyses. Assessment, 27(1), 117–135. https://doi.org/10.1177/1073191117738047
   PubMed Web of Science ®Google Scholar
• McGrath, R. E., Mitchell, M., Kim, B. H., & Hough, L. (2010). Evidence for response bias as a source of error variance in applied assessment. Psychological Bulletin, 136(3), 450–470. https://doi.org/10.1037/a0019216
   PubMed Web of Science ®Google Scholar
• McGrath, R. E., & Wallace, N. (2020). Cross-validation of the VIA inventory of strengths-revised and its short forms. Journal of Personality Assessment 103(1), 120–131. https://doi.org/10.1080/00223891.2019.1705465
   Web of Science ®Google Scholar
• Merritt, S., Huber, K., & Bartkoski, T. (2019). Application of signature strengths at work: A dual-level analysis. The Journal of Positive Psychology, 14(1), 113–124. https://doi.org/10.1080/17439760.2018.1519589
   Web of Science ®Google Scholar
• Murray, D. R., Schaller, M., & Suedfeld, P. (2013). Pathogens and politics: Further evidence that parasite prevalence predicts authoritarianism. PLoS One, 8(5), e62275. https://doi.org/10.1371/journal.pone.0062275
   PubMed Web of Science ®Google Scholar
• Muthén, B., & Asparouhov, T. (2012). Bayesian structural equation modeling: A more flexible representation of substantive theory. Psychological Methods, 17(3), 313–335. https://doi.org/10.1037/a0026802
   PubMed Web of Science ®Google Scholar
• Muthén, L. K., & Muthén, B. O. (2017). Mplus user’s guide (8th ed.). Muthén & Muthén.
   Google Scholar
• Norman, J. (2018, April 6). The religious regions of the U.S. https://news.gallup.com/poll/232223/religious-regions.aspx
   Google Scholar
• O’Connor, B. (2021). EFA.dimensions: Exploratory factor analysis functions for assessing dimensionality, R package version 0.1.7.2. https://CRAN.R-project.org/package=EFA.dimensions
   Google Scholar
• Paulhus, D. L., Harms, P. D., Bruce, M. N., & Lysy, D. C. (2003). The over-claiming technique: Measuring self-enhancement independent of ability. Journal of Personality and Social Psychology, 84(4), 890–904. https://doi.org/10.1037/0022-3514.84.4.890
   PubMed Web of Science ®Google Scholar
• Peterson, C., & Park, N. (2009). Classifying and measuring strengths of character. In C. Snyder & S. Lopez (Eds.), Oxford handbook of positive psychology (pp. 25–33). Oxford University Press.
   Google Scholar
• Peterson, C., & Seligman, M. E. P. (2004). Character strengths and virtues: A handbook and classification. American Psychological Association/Oxford University Press.
   Google Scholar
• Putnick, D. L., & Bornstein, M. H. (2016). Measurement invariance conventions and reporting: The state of the art and future directions for psychological research. Developmental Review: DR, 41, 71–90. https://doi.org/10.1016/j.dr.2016.06.004
   PubMed Web of Science ®Google Scholar
• Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02
   Web of Science ®Google Scholar
• Ruch, W., Weber, M., Park, N., & Peterson, C. (2014). Character strengths in children and adolescents: Reliability and initial validity of the German Values in Action Inventory of Strengths for Youth (German VIA-Youth). European Journal of Psychological Assessment, 30(1), 57–64. https://doi.org/10.1027/1015-5759/a000169
   Web of Science ®Google Scholar
• Smith, G. T., McCarthy, D. M., & Anderson, K. G. (2000). On the sins of short-form development. Psychological Assessment, 12(1), 102–111. https://doi.org/10.1037/1040-3590.12.1.102
   PubMed Web of Science ®Google Scholar
• Soto, C. J., & Tackett, J. L. (2015). Personality traits in childhood and adolescence: Structure, development, and outcomes. Current Directions in Psychological Science, 24(5), 358–362. https://doi.org/10.1177/0963721415589345
   Web of Science ®Google Scholar
• Steiner, M. D., & Grieder, S. G. (2020). EFAtools: An R package with fast and flexible implementations of exploratory factor analysis tools. Journal of Open Source Software, 5(53), 2521. https://doi.org/10.21105/joss.02521
   Google Scholar
• van de Schoot, R., Sijbrandij, M., Depaoli, S., Winter, S. D., Olff, M., & Van Loey, N. E. (2018). Bayesian PTSD-trajectory analysis with informed priors based on a systematic literature search and expert elicitation. Multivariate Behavioral Research, 53(2), 267–291. https://doi.org/10.1080/00273171.2017.1412293
   PubMed Web of Science ®Google Scholar
• Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika, 41, 321–327. https://doi.org/10.1007/BF02293557
   Google Scholar
• Velicer, W. F., Eaton, C. A., & Fava, J. L. (2000). Construct explication through factor or component analysis: A review and evaluation of alternative procedures for determining the number of factors or components. In R. E. Goffin & E. Helmes (Eds.), Problems and solutions in human assessment: Honoring Douglas N. Jackson at seventy (pp. 41–71). Kluwer Academic.
   Google Scholar
• Wanous, J. P., & Hudy, M. J. (2001). Single-item reliability: A replication and extension. Organizational Research Methods, 4(4), 361–375. https://doi.org/10.1177/109442810144003
   Web of Science ®Google Scholar
• Weisberg, Y. J., DeYoung, C. G., & Hirsh, J. B. (2011). Gender differences in personality across the ten aspects of the Big Five. Frontiers in Psychology, 2. https://doi.org/10.3389/fpsyg.2011.00178
   PubMed Web of Science ®Google Scholar
• White, A. E., Kenrick, D. T., & Neuberg, S. L. (2013). Beauty at the ballot box: Disease threats predict preferences for physically attractive leaders. Psychological Science, 24(12), 2429–2436. https://doi.org/10.1177/0956797613493642
   PubMed Web of Science ®Google Scholar
• Zhang, Z., & Yuan, K. (2020). coefficientalpha: Robust coefficient alpha and omega with missing and non-normal. https://CRAN.R-project.org/package=coefficientalpha
   Google Scholar
• Zondervan-Zwijnenburg, M., Peeters, M., Depaoli, S., & Van de Schoot, R. (2017). Where do priors come from? Applying guidelines to construct informative priors in small sample research. Research in Human Development, 14(4), 305–320. https://doi.org/10.1080/15427609.2017.1370966
   Web of Science ®Google Scholar
• Zwick, W. R., & Velicer, W. F. (1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99(3), 432–442. https://doi.org/10.1037/0033-2909.99.3.432
   Web of Science ®Google Scholar