All reviews of published articles are made public. This includes manuscript files, peer review comments, author rebuttals and revised materials. Note: This was optional for articles submitted before 13 February 2023.
Peer reviewers are encouraged (but not required) to provide their names to the authors when submitting their peer review. If they agree to provide their name, then their personal profile page will reflect a public acknowledgment that they performed a review (even if the article is rejected). If the article is accepted, then reviewers who provided their name will be associated with the article itself.
Thank you very much for your patience in revising the manuscript as suggested
[# PeerJ Staff Note - this decision was reviewed and approved by Bob Patton, a PeerJ Section Editor covering this Section #]
Please specify the number of infants included in each of the 3 cohort groups, as already asked by the reviewer in the previous submission. In the revised manuscript I read only the age of infants in the three cohort groups. You may have only tested (several times) one infant at different ages.
Please write the number of infants included in each of the 3 cohort groups (see comments of the referee).
The ms addresses the issue of how to best model quantitatively infant habituation using probabilistic approaches. The topic is important since infant habituation is a critical tool to study the development of perception, attention, and other cognitive abilities in infants. The main result is that partial-pooling models provided more accurate predictions.
The authors compared various additive and multiplicative regression models of habituation to fit looking times of a habituation experiment with infants in three age cohorts (4, 7 and 10 months). They used visual stimuli consisting of rectangles with different luminance, color and orientation. Overall, 359 experiments were performed.
The authors tested 5 probability distributions: truncated normal, truncated normal with exponential mean, lognormal, Weibull, and gamma distribution.
Results showed that partial-pooling models provided more accurate predictions than the no-pooling models, reducing the bias due to over-fitting inherent in no-pooling models. The multiplicative trend models and the gamma trend model in particular provided better data fit, better predictive fit, and lower parameter correlation.
In the Discussion the authors address the potential role of confound stimuli associated with the presentation of test stimuli.
Overall, the ms has been carefully revised relative to previous reviewers’ comments. As a minor comment, I noticed that (unless I missed it!) the number of infants included in each of the 3 cohort groups is not specified, only the number of trials included for each condition in each cohort group is given in Table 1.
One reviewer has raised concerns about your revised manuscript. I kindly invite you to carefully revise your manuscript along the lines suggested by the reviewers in their comments to the previous version of your manuscript.
Please see also the comments to the revised version of the manuscript.
See attachment
See attachment
See attachment
See attachment
Both reviewers have raised concerns about your manuscript. Considering their comments and the editorial criteria of the journal, I would like to invite you to carefully revise your manuscript along the lines suggested.
Please see the annotated PDFs from the reviewers.
Seems OK
Seems OK; design was approved.
OK, likely to have little impact on the field.
I've made comments in the attached review which is to be shared with the author.
No comment.
See attached.
No comment.
See attached.
All text and materials provided via this peer-review history page are made available under a Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.