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Reference 43: R: A language and environment for statistical computing(https://www.r-project.org/)
JMIR Public Health Surveill 2025;11:e67370
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Monte Carlo simulations computed in R (R Foundation for Statistical Computing) were used to estimate the required sample size for our proposed models. Our analyses, based on simulated data, suggest that a total sample size of 300 provides enough statistical power (up to 90%) to detect anticipated effect sizes on primary outcomes of cognitive capacity and cognitive bias based on values from our group and those reported in the literature (CR: d=0.50 and MCT: g=0.27) [9,20,27,31].
JMIR Res Protoc 2025;14:e63269
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Analyses were performed using R (version 4.3.3; R Core Team). App use is described using descriptive statistics.
Of the 43 students, 25 (58%) were classified as low-risk drinkers (AUDIT Score ≤7), 11 (26%) were classified as hazardous drinkers (AUDIT Score between 8 and 15), and 6 (14%) were classified as alcohol dependent drinkers (AUDIT score >15).
JMIR Hum Factors 2025;12:e69873
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The PMIS (Pearson r=−0.76; P
As we examined the sensitivity and specificity data to choose cut scores, we chose to favor sensitivity to minimize missing individuals with true disease in this sample of patients considered high risk because of their cognitive concerns. The cut scores for a positive result on the 5-Cog components were as follows: PMIS ≤6 (range 0-8), Symbol Match ≤25 (range 0-65), and s MCR >5 (range 0-7).
JMIR Res Protoc 2025;14:e60471
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