The Effect of Noninvariance on the Estimation of the Mediated Effect in the Two-Wave Mediation Model

References

• Ahmed, S., Sawatzky, R., Levesque, J. F., Ehrmann-Feldman, D., & Schwartz, C. E. (2014). Minimal evidence of response shift in the absence of a catalyst. Quality of Life Research : An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 23, 2421–2430.
   PubMed Web of Science ®Google Scholar
• Bauer, D. J., & Curran, P. J. (2015). The discrepancy between measurement and modeling in longitudinal data analysis. In J. R. Harring, L. M. Stapleton, & S. N. Beretvas (Eds.), Advances in multilevel modeling for educational research (pp. 3–38). Charlotte, NC: Information Age Publishing.
   Google Scholar
• Behrendt, D., Ebert, D. D., Spiegelhalder, K., & Lehr, D. (2020). Efficacy of a self-help web-based recovery training in improving sleep in workers: Randomized controlled trial in the general working population. Journal of Medical Internet Research, 22, e13346. https://doi.org/10.2196/13346
   PubMedGoogle Scholar
• Bollen, K. A., & Bauldry, S. (2011). Three Cs in measurement models: Causal indicators, composite indicators, and covariates. Psychological Methods, 16, 265–284. https://doi.org/10.1037/a0024448
   PubMed Web of Science ®Google Scholar
• Bollen, K. A., & Diamantopoulos, A. (2017). Notes on measurement theory for causal-formative indicators: A reply to Hardin. Psychological Methods, 22, 605–608. https://doi.org/10.1037/met0000149
   PubMed Web of Science ®Google Scholar
• Byrne, B. M., Shavelson, R. J., & Muthén, B. (1989). Testing for the equivalence of factor covariance and mean structures: the issue of partial measurement invariance. Psychological Bulletin, 105, 456–466. https://doi.org/10.1037/0033-2909.105.3.456
   Web of Science ®Google Scholar
• Carlier, I. V. E., van Eeden, W. A., de Jong, K., Giltay, E. J., van Noorden, M. S., van der Feltz-Cornelis, C., … van Hemert, A. M. (2019). Testing for response shift in treatment evaluation of change in self‐reported psychopathology amongst secondary psychiatric care outpatients. International Journal of Methods in Psychiatric Research, 28, e1785.
   PubMed Web of Science ®Google Scholar
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
   Google Scholar
• Cole, D. A., & Maxwell, S. E. (2003). Testing mediational models with longitudinal data: questions and tips in the use of structural equation modeling. Journal of Abnormal Psychology, 112, 558–577. https://doi.org/10.1037/0021-843X.112.4.558
   PubMed Web of Science ®Google Scholar
• Cole, D. A., & Preacher, K. J. (2014). Manifest variable path analysis: Potentially serious and misleading consequences due to uncorrected measurement error. Psychological Methods, 19, 300–315. https://doi.org/10.1037/a0033805
   PubMed Web of Science ®Google Scholar
• Drennan, J., & Hyde, A. (2008). Controlling response shift bias: The use of the retrospective pre‐test design in the evaluation of a master’s programme. Assessment & Evaluation in Higher Education, 33, 699–709. https://doi.org/10.1080/02602930701773026
   Web of Science ®Google Scholar
• Epskamp, S., Rhemtulla, M., & Borsboom, D. (2017). Generalized network psychometrics: Combining network and latent variable models. Psychometrika, 82, 904–927.
   PubMed Web of Science ®Google Scholar
• Flake, J. K., Pek, J., & Hehman, E. (2017). Construct validation in social and personality research: Current practice and recommendations. Social Psychological and Personality Science, 8, 370–378. https://doi.org/10.1177/1948550617693063
   Web of Science ®Google Scholar
• Fokkema, M., Smits, N., Kelderman, H., & Cuijpers, P. (2013). Response shifts in mental health interventions: An illustration of longitudinal measurement invariance. Psychological Assessment, 25, 520–531. https://doi.org/10.1037/a0031669
   PubMed Web of Science ®Google Scholar
• Fonseca, A., Monteiro, F., Alves, S., Gorayeb, R., & Canavarro, M. C. (2019). Be a Mom, a web-based intervention to prevent postpartum depression: The enhancement of self-regulatory skills and its association with postpartum depressive symptoms. Frontiers in psychology, 265
   Google Scholar
• Georgeson, A. R., Valente, M. J., & Gonzalez, O. (2021). Evaluating response shift in statistical mediation analysis. Advances in Methods and Practices in Psychological Science, 4, 1–14. https://doi.org/10.1177/25152459211012271
   Google Scholar
• Gonzalez, O., & MacKinnon, D. P. (2018). A bifactor approach to model multifaceted constructs in statistical mediation analysis. Educational and Psychological Measurement, 78, 5–31. https://doi.org/10.1177/0013164416673689
   PubMed Web of Science ®Google Scholar
• Gonzalez, O., & MacKinnon, D. P. (2021). The measurement of the mediator and its influence on statistical mediation conclusions. Psychological Methods, 26, 1–17. https://doi.org/10.1037/met0000263
   PubMed Web of Science ®Google Scholar
• Gonzalez, O., O’Rourke, H. P., Wurpts, I. C., & Grimm, K. J. (2018). Analyzing Monte Carlo simulation studies with classification and regression trees. Structural Equation Modeling: A Multidisciplinary Journal, 25, 403–413. https://doi.org/10.1080/10705511.2017.1369353
   Web of Science ®Google Scholar
• Guenole, N., & Brown, A. (2014). The consequences of ignoring measurement invariance for path coefficients in structural equation models. Frontiers in Psychology, 5, 980. https://doi.org/10.3389/fpsyg.2014.00980
   PubMed Web of Science ®Google Scholar
• Hoogland, J. J., & Boomsma, A. (1998). Robustness studies in covariance structure modeling: An overview and a meta-analysis. Sociological Methods & Research, 26, 329–367. https://doi.org/10.1177/0049124198026003003
   Web of Science ®Google Scholar
• Howard, G. S. (1980). Response-shift bias: A problem in evaluating interventions with pre/post self-reports. Evaluation Review, 4, 93–106. https://doi.org/10.1177/0193841X8000400105
   Web of Science ®Google Scholar
• Imai, K., Keele, L., & Tingley, D. (2010). A general approach to causal mediation analysis. Psychological Methods, 15, 309–334. https://doi.org/10.1037/a0020761
   PubMed Web of Science ®Google Scholar
• Ledgerwood, A., & Shrout, P. E. (2011). The trade-off between accuracy and precision in latent variable models of mediation processes. Journal of Personality and Social Psychology, 101, 1174–1188.
   PubMed Web of Science ®Google Scholar
• MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. New York, NY: Taylor & Francis/Erlbaum.
   Google Scholar
• MacKinnon, D. P., & Dwyer, J. H. (1993). Estimating mediated effects in prevention studies. Evaluation Review, 17, 144–158. https://doi.org/10.1177/0193841X9301700202
   Web of Science ®Google Scholar
• MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A comparison of methods to test mediation and other intervening variable effects. Psychological Methods, 7, 83–104. https://doi.org/10.1037/1082-989X.7.1.83
   PubMed Web of Science ®Google Scholar
• MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39, 99–128. https://doi.org/10.1207/s15327906mbr3901_4
   PubMed Web of Science ®Google Scholar
• Mayer, A., Thoemmes, F., Rose, N., Steyer, R., & West, S. G. (2014). Theory and analysis of total, direct, and indirect causal effects. Multivariate Behavioral Research, 49, 425–442. https://doi.org/10.1080/00273171.2014.931797
   PubMed Web of Science ®Google Scholar
• McNeish, D., & Wolf, M. G. (2020). Thinking twice about sum scores. Behavior Research Methods, 52, 2287–2305. https://doi.org/10.3758/s13428-020-01398-0
   PubMed Web of Science ®Google Scholar
• Millsap, R. E. (2011). Statistical approaches to measurement invariance. New York, NY: Routledge.
   Google Scholar
• Millsap, R. E., & Kwok, O.-M. (2004). Evaluating the impact of partial factorial invariance on selection in two populations. Psychological Methods, 9, 93–115. https://doi.org/10.1037/1082-989X.9.1.93
   PubMed Web of Science ®Google Scholar
• Millsap, R. E., & Olivera-Aguilar, M. (2012). Investigating measurement invariance using confirmatory factor analysis. In R. H. Hoyle (Ed.), Handbook of structural equation modeling (pp. 380–392). New York, NY: Guilford Press.
   Google Scholar
• Morin, L., Grégoire, S., & Lachance, L. (2021). Processes of change within acceptance and commitment therapy for university students: Preliminary evidence from a randomized controlled trial. Journal of American College Health, 69, 1–10. https://doi.org/10.1080/07448481.2019.1705828
   PubMed Web of Science ®Google Scholar
• Olivera-Aguilar, M., Rikoon, S. H., Gonzalez, O., Kisbu-Sakarya, Y., & MacKinnon, D. P. (2018). Bias, Type I error rates, and statistical power of a latent mediation model in the presence of violations of invariance. Educational and Psychological Measurement, 78, 460–481. https://doi.org/10.1177/0013164416684169
   PubMed Web of Science ®Google Scholar
• Oort, F. J. (2005). Using structural equation modeling to detect response shifts and true change. Quality of Life Research, 14, 587–598. https://doi.org/10.1007/s11136-004-0830-y
   PubMed Web of Science ®Google Scholar
• Pearl, J. (2001, August). Direct and indirect effects. In Proceedings of the seventeenth conference on uncertainty in artificial intelligence (pp. 411–420). San Francisco, CA: Morgan Kaufmann Publishers Inc. arXiv:1301.2300
   Google Scholar
• Quigley, L., Dozois, D. J. A., Bagby, R. M., Lobo, D. S. S., Ravindran, L., & Quilty, L. C. (2019). Cognitive change in cognitive-behavioural therapy v. pharmacotherapy for adult depression: a longitudinal mediation analysis. Psychological Medicine, 49, 2626–2634. https://doi.org/10.1017/S0033291718003653
   PubMed Web of Science ®Google Scholar
• Rapkin, B. D., & Schwartz, C. E. (2019). Advancing quality-of-life research by deepening our understanding of response shift: A unifying theory of appraisal. Quality of Life Research : An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 28, 2623–2630. https://doi.org/10.1007/s11136-019-02248-z
   PubMed Web of Science ®Google Scholar
• Rapkin, B. D., & Schwartz, C. E. (2021). What should progress in response-shift research look like? Quality of Life Research, 30, 3359–3361. https://doi.org/10.1007/s11136-021-02962-7
   PubMed Web of Science ®Google Scholar
• Rhemtulla, M., van Bork, R., & Borsboom, D. (2020). Worse than measurement error: Consequences of inappropriate latent variable measurement models. Psychological Methods, 25, 30–45. https://doi.org/10.1037/met0000220
   PubMed Web of Science ®Google Scholar
• Robins, J. M., & Greenland, S. (1992). Identifiability and exchangeability for direct and indirect effects. Epidemiology (Cambridge, Mass.), 3, 143–155. https://doi.org/10.1097/00001648-199203000-00013
   PubMed Web of Science ®Google Scholar
• Sajobi, T. T., Brahmbatt, R., Lix, L. M., Zumbo, B. D., & Sawatzky, R. (2018). Scoping review of response shift methods: Current reporting practices and recommendations. Quality of Life Research, 27, 1133–1146.
   PubMed Web of Science ®Google Scholar
• Savalei, V. (2019). A comparison of several approaches for controlling measurement error in small samples. Psychological Methods, 24, 352–370. https://doi.org/10.1037/met0000181
   PubMed Web of Science ®Google Scholar
• Smith, D., Woodman, R., Harvey, P., & Battersby, M. (2016). Self-perceived distress and impairment in problem gamblers: A study of pre- to post-treatment measurement invariance. Journal of Gambling Studies, 32, 1065–1078. https://doi.org/10.1007/s10899-016-9598-6
   PubMed Web of Science ®Google Scholar
• Sprangers, M. A., & Schwartz, C. E. (1999). Integrating response shift into health-related quality of life research: A theoretical model. Social Science & Medicine (1982), 48, 1507–1515. https://doi.org/10.1007/s11136-017-1751-x.
   PubMed Web of Science ®Google Scholar
• Tofighi, D., & MacKinnon, D. P. (2011). RMediation: An R package for mediation analysis confidence intervals. Behavior Research Methods, 43, 692–700. https://doi.org/10.3758/s13428-011-0076-x
   PubMed Web of Science ®Google Scholar
• Valente, M. J., & MacKinnon, D. P. (2017). Comparing models of change to estimate the mediated effect in the pretest-posttest control group design. Structural Equation Modeling : A Multidisciplinary Journal, 24, 428–450. https://doi.org/10.1080/10705511.2016.1274657
   PubMed Web of Science ®Google Scholar
• Valente, M. J., MacKinnon, D. P., & Mazza, G. L. (2020). A viable alternative when propensity scores fail: Evaluation of inverse propensity weighting and sequential G-estimation in a two-wave mediation model. Multivariate Behavioral Research, 55, 165–187. https://doi.org/10.1080/00273171.2019.1614429
   PubMed Web of Science ®Google Scholar
• Valeri, L., & VanderWeele, T. J. (2013). Mediation analysis allowing for exposure–mediator interactions and causal interpretation: Theoretical assumptions and implementation with SAS and SPSS macros. Psychological Methods, 18, 137–150. https://doi.org/10.1037/a0031034
   PubMed Web of Science ®Google Scholar
• Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organ. Res. Methods, 3, 4–70. https://doi.org/10.1177/109442810031002
   Web of Science ®Google Scholar
• Vanier, A., Oort, F. J., McClimans, L., Ow, N., Gulek, B. G., Böhnke, J. R., … Mayo, N. (2021). Response shift in patient-reported outcomes: Definition, theory, and a revised model. Quality of Life Research, 30, 3309–3322. https://doi.org/10.1007/s11136-021-02846-w
   PubMedGoogle Scholar
• Verdam, M. G. E., van Ballegooijen, W., Holtmaat, C. J. M., Knoop, H., Lancee, J., Oort, F. J., … Sprangers, M. A. G. (2021). Re-evaluating randomized clinical trials of psychological interventions: Impact of response shift on the interpretation of trial results. PloS One, 16, e0252035. https://doi.org/10.1371/journal.pone.0252035
   PubMed Web of Science ®Google Scholar
• Williams, J., Jones, S. B., Pemberton, M. R., Bray, R. M., Brown, J. M., & Vandermaas-Peeler, R. (2010). Measurement invariance of alcohol use motivations in junior military personnel at risk for depression or anxiety. Addictive Behaviors, 35, 444–451. https://doi.org/10.1016/j.addbeh.2009.12.012
   PubMed Web of Science ®Google Scholar
• Wu, P. C. (2016). Response shifts in depression intervention for early adolescents. Journal of Clinical Psychology, 72, 663–675. https://doi.org/10.1002/jclp.22291
   PubMed Web of Science ®Google Scholar
• Xu, J., Zhang, Q., & Yang, Y. (2020). Impact of violations of measurement invariance in cross-lagged panel mediation models. Behavior Research Methods, 52, 2623–2645.
   PubMed Web of Science ®Google Scholar
• Yuan, Y., & MacKinnon, D. P. (2009). Bayesian mediation analysis. Psychological Methods, 14, 301–322. https://doi.org/10.1037/a0016972
   PubMed Web of Science ®Google Scholar