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As this paper compares the service utilization between members and non-members, there is a possible bias in data analysis due to adverse selection.
Furthermore, in the study by Sun et al., non-downstaged patients presented with a higher initial volume than the downstaged group, what could have led to a bias in data analysis.
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Such a bias is classical in data analysis.
We will account for this bias risk during recruitment and in data analysis.
This bias could have influenced the data collection (two of the authors were interviewers) and the analysis (all three authors were involved in data analysis).
Yet students need grounding in data analysis.
We therefore also compare these influences with tag-position bias to evaluate the relative size of the effect of tag-position bias in MPSS data analysis.
If one wants to see effects of tissue repair, to prevent any bias in the data analysis, one should avoid any data collection from the boundary region between the direct impact site and the surrounding unimpacted areas.
Because the detection of hearing impairment is associated with decreased levels of the DPOAE response, rejecting data with low SNR would introduce a serious bias in the data analysis.
This work has some limitations: the first one is the retrospective nature of the study, which may determine a bias in the data analysis and the second is the modest number of the patients analyzed.
There is a possibility of selection bias in the data analysis cohort as a high risk group of 19 patients with 25 HF events and 11 deaths, with 4 HF readmissions and 6 deaths within 30 days post-discharge, had to be excluded due to unavailability of device data on the day of discharge.
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