Sample size estimation: How many individuals should be studied?

被引：538

作者：

Eng, J ^{[1
]}

机构：

[1] Johns Hopkins Univ, Russell H Morgan Dept Radiol & Radiol Sci, Baltimore, MD 21287 USA

来源：

RADIOLOGY | 2003年 / 227卷 / 02期

关键词：

radiology and radiologists; research; statistical analysis;

D O I：

10.1148/radiol.2272012051

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

The number of individuals to include in a research study, the sample size of the study, is an important consideration in the design of many clinical studies. This article reviews the basic factors that determine an appropriate sample size and I provides methods for its calculation in some simple, yet common, cases. Sample size is closely tied to statistical power, which is the ability of a study to enable detection of a statistically significant difference when there truly is one. A trade-off exists between a feasible sample size and adequate statistical power. Strategies for reducing the necessary sample size while maintaining a reasonable power will also be discussed.

引用

页码：309 / 313

页数：5

共 19 条

[1]

Altman DG, 1990, PRACTICAL STAT MED R

[2]

[Anonymous], 2007, DESIGNING CLIN RES P

[3]

BOND J, POWER CALCULATOR

[4] ARE ALL SIGNIFICANT P-VALUES CREATED EQUAL - THE ANALOGY BETWEEN DIAGNOSTIC-TESTS AND CLINICAL RESEARCH [J].

BROWNER, WS ;

NEWMAN, TB .

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 1987, 257 (18) :2459-2463

[5]

Daniel WW, 1999, BIOSTATISTICS FDN AN, p[180, 268]

[6]

FEINSTEIN AR, 2002, PRINCIPLES MED STAT, P503

[7]

Fleiss J., 1981, STAT METHODS RATES P, V2nd ed., P45

[8] IMPORTANCE OF BETA, TYPE-II ERROR AND SAMPLE-SIZE IN DESIGN AND INTERPRETATION OF RANDOMIZED CONTROL TRIAL - SURVEY OF 71 NEGATIVE TRIALS [J].

FREIMAN, JA ;

CHALMERS, TC ;

SMITH, H ;

KUEBLER, RR .

NEW ENGLAND JOURNAL OF MEDICINE, 1978, 299 (13) :690-694

[9] REPEATED MEASURES IN CLINICAL-TRIALS - ANALYSIS USING MEAN SUMMARY STATISTICS AND ITS IMPLICATIONS FOR DESIGN [J].

FRISON, L ;

POCOCK, SJ .

STATISTICS IN MEDICINE, 1992, 11 (13) :1685-1704

[10] The abuse of power: The pervasive fallacy of power calculations for data analysis [J].

Hoenig, JM ;

Heisey, DM .

AMERICAN STATISTICIAN, 2001, 55 (01) :19-24

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