Review and recommendations for univariate statistical analysis of spherical equivalent prediction error for IOL power calculations

异方差 统计 单变量 数学 I类和II类错误 标准差 正态分布 高斯分布 样本量测定 统计能力 多元正态分布 覆盖概率 置信区间 多元统计 物理 量子力学
作者
Jack T. Holladay,Rand R. Wilcox,Douglas D. Koch,Li Wang
出处
期刊:Journal of Cataract and Refractive Surgery [Lippincott Williams & Wilkins]
卷期号:47 (1): 65-77 被引量:143
标识
DOI:10.1097/j.jcrs.0000000000000370
摘要

Purpose: To provide a reference for study design comparing intraocular lens (IOL) power calculation formulas, to show that the standard deviation (SD) of the prediction error (PE) is the single most accurate measure of outcomes, and to provide the most recent statistical methods to determine P values for type 1 errors. Setting: Baylor College of Medicine, Houston, Texas, and University of Southern California, Los Angeles, California, USA. Design: Retrospective consecutive case series. Methods: Two datasets comprised of 5200 and 13 301 single eyes were used. The SDs of the PEs for 11 IOL power calculation formulas were calculated for each dataset. The probability density functions of signed and absolute PE were determined. Results: None of the probability distributions for any formula in either dataset was normal (Gaussian). All the original signed PE distributions were not normal, but symmetric and leptokurtotic (heavy tailed) and had higher peaks than a normal distribution. The absolute distributions were asymmetric and skewed to the right. The heteroscedastic method was much better at controlling the probability of a type I error than older methods. Conclusions: (1) The criteria for patient and data inclusion were outlined; (2) the appropriate sample size was recommended; (3) the requirement that the formulas be optimized to bring the mean error to zero was reinforced; (4) why the SD is the single best parameter to characterize the performance of an IOL power calculation formula was demonstrated; and (5) and using the heteroscedastic statistical method was the preferred method of analysis was shown.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
千空完成签到 ,获得积分10
2秒前
3秒前
流砂完成签到,获得积分10
6秒前
严采波完成签到,获得积分10
7秒前
张勇振完成签到,获得积分10
9秒前
9秒前
HelloFM完成签到,获得积分10
9秒前
savona7发布了新的文献求助10
11秒前
wang完成签到,获得积分10
12秒前
A羽发布了新的文献求助10
15秒前
大模型应助dr_zhoujielong采纳,获得10
16秒前
王正正完成签到,获得积分10
17秒前
Jeamren完成签到,获得积分10
20秒前
seed完成签到 ,获得积分10
22秒前
mikaqyan完成签到,获得积分10
28秒前
savona7完成签到,获得积分10
28秒前
架嘉驾完成签到,获得积分10
29秒前
搞怪孤丝完成签到 ,获得积分10
29秒前
cdc完成签到 ,获得积分10
29秒前
面汤完成签到 ,获得积分10
30秒前
31秒前
阔达的海完成签到,获得积分10
32秒前
一切顺利完成签到 ,获得积分10
33秒前
沉默含海完成签到 ,获得积分10
34秒前
从容的念芹完成签到 ,获得积分10
36秒前
无奈盼易完成签到,获得积分10
38秒前
星星完成签到,获得积分10
39秒前
Sunny完成签到,获得积分10
40秒前
科研通AI6.3应助丑小鸭采纳,获得30
45秒前
小屋完成签到,获得积分10
47秒前
48秒前
rayqiang完成签到,获得积分0
52秒前
rayq完成签到,获得积分10
52秒前
sagitar应助科研通管家采纳,获得20
52秒前
大模型应助科研通管家采纳,获得10
52秒前
52秒前
52秒前
53秒前
53秒前
Orange应助科研通管家采纳,获得10
53秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Nondestructive Testing Handbook: Vol. 4, Thermal and Infrared Testing (IR), 4th ed 800
Understanding Acculturation: The Process of Cultural Adjustment as Applied to International Migration 700
作者名:Kristopher P. Plain,悉尼大学的,目前只能查到其四篇论文,想找到其博士论文 590
Évora na Idade Média 555
Soil mites of the family Rhagidiidae (Actinedida: Eupodoidea). Morphology, Systematics, Ecology 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7370883
求助须知:如何正确求助?哪些是违规求助? 8978490
关于积分的说明 19087561
捐赠科研通 7012975
什么是DOI,文献DOI怎么找? 3224993
关于科研通互助平台的介绍 2388627
邀请新用户注册赠送积分活动 2205666