Thank you again for the detailed revisions! All comments have been addressed and I don’t have anything else to add. Best of luck with your research!

Best,
Lewend

I read the revised version of the manuscript with interest. The authors have done a great job in responding to the comments of the editor and reviewers. The reformulation of the hypotheses, the planned multiverse analyses, and the steps taken to deal with the risk of bias improve the manuscript considerably. 

I do, however, have a reservation about the script. I am not familiar with doing RI-CLPM with R (but more on MPlus), but the script seems somewhat different from what I am used to. In particular, it doesn't include the between components, allowing to distinguish between variance from within variance. But I am relying on Hamaker et al.(2015) and Mulder & Hamaker (2021). Perhaps the authors rely on other references? If so, it may be interesting to cite them.

References

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

Mulder, J. D., & Hamaker, E. L. (2021). Three Extensions of the Random Intercept Cross-Lagged Panel Model. Structural Equation Modeling: A Multidisciplinary Journal, 28(4), 638–648. https://doi.org/10.1080/10705511.2020.1784738

The research question is not really new, but it is interesting and may be of some importance in establishing potential bidirectionality between risk perception and compliance with preventive behaviour on a longitudinal and (fairly) representative database. 
The hypotheses are credible and precise. However, hypothesis H3 should be introduced and justified.
The data has already been collected and the targeted measures from the first wave have been used in three manuscripts (published or pre-printed). In one of these manuscripts, the authors even test the link between perceived risk and compliance. Although the authors state this, it is a concern to me. Indeed, the authors have already tested H1a, so the level of prior knowledge of the data is not satisfactory. The authors state that it is not exactly the same items that have been used; but this poses a limit to the measurement if the authors consider that it is not the same concepts, or if it is conceptually the same thing, then the authors have already tested H1a. 
Second, there are discrepancies between the theoretical reasoning and the methodology used. In particular, when perceived risk is defined, it is defined as a risk to oneself. On the other hand, it is measured using several items relating to the risk associated with the disease for one's own health, that of others, and even for one's life in general. This should be specified if and why differences in effects can be expected. Second, and similarly, compliance involves a range of different behaviours. Some authors have argued for a distinction between different preventive behaviours (e.g., distancing from hygiene). The authors should have taken this into account in order to shed more light on their research question.
Third, It is not clear which participants would be retained (only participants who responded to all four waves?) and no power analysis is carried out to ensure the relevance of the sample available.

To conclude, I have serious reservations about whether these hypotheses, with these data, can be tested in an RR format. This does not preclude the interest of the question, but rather the appropriateness of the publication process.

Thank you for the opportunity to review the Stage 1 report of “Relationship between perceived risk and compliance to infection control measures during the first year of a pandemic”. The registered report proposes to test the association between risk perception and compliance with covid-19 control measures among a representative Norwegian sample, while also testing how this association changes over time. The report is concise, well-structured, easy to read, and clearly spells out the contribution to the literature. This is my first time reviewing a registered report based on secondary data. The authors are very transparent in reporting prior knowledge with the data that they plan to use. Overall, I think this report generally meets the Stage 1 criteria, but I have some minor comments and suggestions that I hope will be useful.

• The authors specify using a p-value cut-off of 5%. But given the very large sample size (in each time point), I wonder whether this cut-off should be reduced. Some have argued that when sample size is very large, p-values right under .05 (e.g., .04) might be taken as evidence for the null (e.g., see: https://journals.sagepub.com/doi/10.1177/25152459221080396).
• This brings me to my next comment: In Table 3, if I have interpreted this correctly, the authors specify that lack of support for a hypothesis will be interpreted as indicating the absence of an association. This means that p-values right below 5% would be taken as evidence for an association when in fact they might indicate evidence for the absence of an association. I’ve never worked with sample sizes this large, and I have no experience with the methodology proposed in this study, but I wonder if one might want to complement traditional null hypothesis significance testing with alternative methods that quantify evidence for the null more directly (e.g., equivalence testing or Bayesian analysis).
• On page 6, the authors write that they will also test the reversed relationship, that is, whether compliance predicts perceived risk. Although I think I know why the authors want to test this, I think it might be good to provide a brief justification, and perhaps to also explain why they want to test it non-directionally.
• Just a suggestion, and I don’t mean to complicate things, but it would be helpful to see the whole Results section written out based on simulated data and share the analytical code (by uploading it to the OSF page). This would make it easier to compare the Stage 1 report with the Stage 2 report and would allow the authors to potentially get feedback on their analysis script and detect potential errors.
• This is a very minor suggestion, but I think this part on page 6 can be removed: “We will use a registered report publication process to enhance the transparency and rigor of our research methodology, study design and analysis plan. This approach ensures that the significance of our study is evaluated based on the research question and methodology, rather than the outcomes.”
• On page 6 there is a missing closing parenthesis (in “(H3”).

I wish the authors good luck with their paper!

Kind regards,
Lewend Mayiwar