Journal article
Generalized Confidence Intervals for Ratios of Standard Deviations Based on Log-Normal Distribution when Times Follow Weibull Distributions
Journal of medical systems, Vol.48(1), 58
06/01/2024
DOI: 10.1007/s10916-024-02073-z
PMID: 38822876
Abstract
Modern anesthetic drugs ensure the efficacy of general anesthesia. Goals include reducing variability in surgical, tracheal extubation, post-anesthesia care unit, or intraoperative response recovery times. Generalized confidence intervals based on the log-normal distribution compare variability between groups, specifically ratios of standard deviations. The alternative statistical approaches, performing robust variance comparison tests, give P-values, not point estimates nor confidence intervals for the ratios of the standard deviations. We performed Monte-Carlo simulations to learn what happens to confidence intervals for ratios of standard deviations of anesthesia-associated times when analyses are based on the log-normal, but the true distributions are Weibull. We used simulation conditions comparable to meta-analyses of most randomized trials in anesthesia,
and coefficients of variation
. The estimates of the ratios of standard deviations were positively biased, but slightly, the ratios being 0.11% to 0.33% greater than nominal. In contrast, the 95% confidence intervals were very wide (i.e., > 95% of P ≥ 0.05). Although substantive inferentially, the differences in the confidence limits were small from a clinical or managerial perspective, with a maximum absolute difference in ratios of 0.016. Thus, P < 0.05 is reliable, but investigators should plan for Type II errors at greater than nominal rates.
Details
- Title: Subtitle
- Generalized Confidence Intervals for Ratios of Standard Deviations Based on Log-Normal Distribution when Times Follow Weibull Distributions
- Creators
- Pei-Fu Chen - Far Eastern Memorial HospitalFranklin Dexter - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of medical systems, Vol.48(1), 58
- DOI
- 10.1007/s10916-024-02073-z
- PMID
- 38822876
- ISSN
- 0148-5598
- eISSN
- 1573-689X
- Language
- English
- Date published
- 06/01/2024
- Academic Unit
- Anesthesia
- Record Identifier
- 9984634944502771
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