7  Further reading and references

7.1 Where to start

  • The Open Handbook of Experience Sampling Methodology (Myin-Germeys & Kuppens, 2026). A free, step-by-step guide from question to analysis. The third edition is open access and includes chapters on sample size, passive sensing and dyadic ESM. Publisher page
  • Intensive Longitudinal Methods (Bolger & Laurenceau, 2013). The standard textbook on analysis, with worked examples.
  • Handbook of Research Methods for Studying Daily Life (Mehl & Conner, 2012). Broad coverage of methods, measures and analysis.
  • So you want to do ESM? (Fritz et al., 2024). A compact practical overview of ten essential topics.
  • Preprocessing ESM data (Revol et al., 2024). A step-by-step framework, the esmtools R package and a tutorial website.

7.2 References

Asparouhov, T., Hamaker, E. L., & Muthén, B. (2018). Dynamic structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 25(3), 359–388. https://doi.org/10.1080/10705511.2017.1406803
Bolger, N., Davis, A., & Rafaeli, E. (2003). Diary methods: Capturing life as it is lived. Annual Review of Psychology, 54, 579–616. https://doi.org/10.1146/annurev.psych.54.101601.145030
Bolger, N., & Laurenceau, J.-P. (2013). Intensive longitudinal methods: An introduction to diary and experience sampling research. Guilford Press.
Cranford, J. A., Shrout, P. E., Iida, M., Rafaeli, E., Yip, T., & Bolger, N. (2006). A procedure for evaluating sensitivity to within-person change: Can mood measures in diary studies detect change reliably? Personality and Social Psychology Bulletin, 32(7), 917–929. https://doi.org/10.1177/0146167206287721
Delespaul, P. A. E. G. (1995). Assessing schizophrenia in daily life: The experience sampling method. Maastricht University Press.
Driver, C. C., Oud, J. H. L., & Voelkle, M. C. (2017). Continuous time structural equation modeling with R package ctsem. Journal of Statistical Software, 77(5), 1–35. https://doi.org/10.18637/jss.v077.i05
Eisele, G., Hiekkaranta, A., Kunkels, Y. K., Aan Het Rot, M., Van Ballegooijen, W., Bartels, S. L., Bastiaansen, J. A., Beymer, P. N., Bylsma, L. M., Carpenter, R. W., et al. (2025). ESM-q: A consensus-based quality assessment tool for experience sampling method items. Behavior Research Methods, 57(4), 124.
Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 12(2), 121–138. https://doi.org/10.1037/1082-989X.12.2.121
Epskamp, S., Waldorp, L. J., Mõttus, R., & Borsboom, D. (2018). The Gaussian graphical model in cross-sectional and time-series data. Multivariate Behavioral Research, 53(4), 453–480. https://doi.org/10.1080/00273171.2018.1454823
Fritz, J., Piccirillo, M. L., Cohen, Z. D., Frumkin, M., Kirtley, O., Moeller, J., Neubauer, A. B., Norris, L. A., Schuurman, N. K., Snippe, E., & Bringmann, L. F. (2024). So you want to do ESM? 10 essential topics for implementing the experience-sampling method. Advances in Methods and Practices in Psychological Science, 7(3). https://doi.org/10.1177/25152459241267912
Gates, K. M., & Molenaar, P. C. M. (2012). Group search algorithm recovers effective connectivity maps for individuals in homogeneous and heterogeneous samples. NeuroImage, 63(1), 310–319. https://doi.org/10.1016/j.neuroimage.2012.06.026
Geldhof, G. J., Preacher, K. J., & Zyphur, M. J. (2014). Reliability estimation in a multilevel confirmatory factor analysis framework. Psychological Methods, 19(1), 72–91. https://doi.org/10.1037/a0032138
Hamaker, E. L. (2012). Why researchers should think “within-person”: A paradigmatic rationale. In M. R. Mehl & T. S. Conner (Eds.), Handbook of research methods for studying daily life (pp. 43–61). Guilford Press.
Hamaker, E. L., Kuiper, R. M., & Grasman, R. P. P. P. (2015). A critique of the cross-lagged panel model. Psychological Methods, 20(1), 102–116. https://doi.org/10.1037/a0038889
Hedeker, D., Mermelstein, R. J., & Demirtas, H. (2008). An application of a mixed-effects location scale model for analysis of ecological momentary assessment (EMA) data. Biometrics, 64(2), 627–634. https://doi.org/10.1111/j.1541-0420.2007.00924.x
Kirtley, O. J., Lafit, G., Achterhof, R., Hiekkaranta, A. P., & Myin-Germeys, I. (2021). Making the black box transparent: A template and tutorial for registration of studies using experience-sampling methods. Advances in Methods and Practices in Psychological Science, 4(1). https://doi.org/10.1177/2515245920924686
Klasnja, P., Hekler, E. B., Shiffman, S., Boruvka, A., Almirall, D., Tewari, A., & Murphy, S. A. (2015). Microrandomized trials: An experimental design for developing just-in-time adaptive interventions. Health Psychology, 34(Suppl.), 1220–1228. https://doi.org/10.1037/hea0000305
Lafit, G., Adolf, J. K., Dejonckheere, E., Myin-Germeys, I., Viechtbauer, W., & Ceulemans, E. (2021). Selection of the number of participants in intensive longitudinal studies: A user-friendly shiny app and tutorial for performing power analysis in multilevel regression models that account for temporal dependencies. Advances in Methods and Practices in Psychological Science, 4(1). https://doi.org/10.1177/2515245920978738
Langener, A. M., Siepe, B. S., Elsherif, M., Niemeijer, K., Andresen, P. K., Akre, S., Bringmann, L. F., Cohen, Z. D., Choukas, N. R., Drexl, K., et al. (2024). A template and tutorial for preregistering studies using passive smartphone measures. Behavior Research Methods, 56(8), 8289–8307.
Larson, R., & Csikszentmihalyi, M. (1983). The experience sampling method. New Directions for Methodology of Social and Behavioral Science, 15, 41–56.
Lewetz, D., & Stieger, S. (2024). ESMira: A decentralized open-source application for collecting experience sampling data. Behavior Research Methods, 56(5), 4421–4434. https://doi.org/10.3758/s13428-023-02194-2
McNeish, D., & Hamaker, E. L. (2020). A primer on two-level dynamic structural equation models for intensive longitudinal data in Mplus. Psychological Methods, 25(5), 610–635. https://doi.org/10.1037/met0000250
Mehl, M. R., & Conner, T. S. (Eds.). (2012). Handbook of research methods for studying daily life. Guilford Press.
Molenaar, P. C. M. (2004). A manifesto on psychology as idiographic science: Bringing the person back into scientific psychology, this time forever. Measurement: Interdisciplinary Research and Perspectives, 2(4), 201–218. https://doi.org/10.1207/s15366359mea0204_1
Myin-Germeys, I., & Kuppens, P. (Eds.). (2026). The open handbook of experience sampling methodology (3rd ed.). Leuven University Press. https://lup.be/book/the-open-handbook-of-experience-sampling-methodology-third-edition/
Nahum-Shani, I., Smith, S. N., Spring, B. J., Collins, L. M., Witkiewitz, K., Tewari, A., & Murphy, S. A. (2018). Just-in-time adaptive interventions (JITAIs) in mobile health: Key components and design principles for ongoing health behavior support. Annals of Behavioral Medicine, 52(6), 446–462. https://doi.org/10.1007/s12160-016-9830-8
Revol, J., Carlier, C., Lafit, G., Verhees, M., Sels, L., & Ceulemans, E. (2024). Preprocessing experience-sampling-method data: A step-by-step framework, tutorial website, R package, and reporting templates. Advances in Methods and Practices in Psychological Science, 7(4). https://doi.org/10.1177/25152459241256609
Rights, J. D., & Sterba, S. K. (2019). Quantifying explained variance in multilevel models: An integrative framework for defining R-squared measures. Psychological Methods, 24(3), 309–338. https://doi.org/10.1037/met0000184
Schuurman, N. K., & Hamaker, E. L. (2019). Measurement error and person-specific reliability in multilevel autoregressive modeling. Psychological Methods, 24(1), 70–91. https://doi.org/10.1037/met0000188
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Wrzus, C., & Neubauer, A. B. (2023). Ecological momentary assessment: A meta-analysis on designs, samples, and compliance across research fields. Assessment, 30(3), 825–846. https://doi.org/10.1177/10731911211067538