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[分享] Sample Size Calculations in Clinical Research

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epiman 发表于 2015-10-12 15:31:42 | 显示全部楼层 |阅读模式

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Sample Size Calculations for Clustered and Longitudinal Outcomes in Clinical Research
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- U* ^2 r# H6 d" p4 ~1 Q" \2 vFeatures
  • Discusses sample size determination for independent outcomes as well as variants of clustered trials, including one- and two-sample trials for continuous and binary outcomes, stratified cluster design, and nonparametric approaches
  • Presents sample size methods based on summary statistics of longitudinal outcomes
  • Explains how to determine sample size using GEE approaches for various types of correlated outcomes, including continuous, binary, and count
  • Describes mixed-effects model approaches for randomized clinical trials with two level data structures
  • Extends the mixed-effects model sample size approaches to scenarios where three level data structures are involved in randomized trials; W  L- X/ ^0 h% N
SummaryAccurate sample size calculation ensures that clinical studies have adequate power to detect clinically meaningful effects. This results in the efficient use of resources and avoids exposing a disproportionate number of patients to experimental treatments caused by an overpowered study.
: J- n" U! r% g2 o! J# JSample Size Calculations for Clustered and Longitudinal Outcomes in Clinical Research explains how to determine sample size for studies with correlated outcomes, which are widely implemented in medical, epidemiological, and behavioral studies.
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! V$ a9 L6 T+ G* i- ^The book focuses on issues specific to the two types of correlated outcomes: longitudinal and clustered. For clustered studies, the authors provide sample size formulas that accommodate variable cluster sizes and within-cluster correlation. For longitudinal studies, they present sample size formulas to account for within-subject correlation among repeated measurements and various missing data patterns. For multiple levels of clustering, the level at which to perform randomization actually becomes a design parameter. The authors show how this can greatly impact trial administration, analysis, and sample size requirement.% p* w, L2 }0 T& Q1 Z8 t+ `
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Addressing the overarching theme of sample size determination for correlated outcomes, this book provides a useful resource for biostatisticians, clinical investigators, epidemiologists, and social scientists whose research involves trials with correlated outcomes. Each chapter is self-contained so readers can explore topics relevant to their research projects without having to refer to other chapters.
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Sample Size Calculations in Clinical Research.pdf

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 楼主| epiman 发表于 2015-10-12 15:33:23 | 显示全部楼层
Table of Contents
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8 z$ w' U! D  K/ j0 }* B5 P8 c, QSample Size Determination for Independent Outcomes 0 x4 g# M( J/ X! J0 f. i
Introduction / _$ T/ \# z% R5 n" i
Precision Analysis ' M2 Y/ \3 R: b5 M) I
Power Analysis
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7 R7 l+ X) b' ^5 p( ISample Size Determination for Clustered Outcomes
3 x/ w: {$ h' Z4 i1 qIntroduction ' [, J9 ]% V: K+ @' c3 {4 x+ l
One-Sample Clustered Continuous Outcomes
& {# W' k8 W- C! {One-Sample Clustered Binary Outcomes : z* F( F- d) }. |
Two-Sample Clustered Continuous Outcomes
6 e; y. w" w7 B( `5 ?+ A! UTwo-Sample Clustered Binary Outcomes
. i5 N% J) y, O" l) t+ I! K! T/ PStratified Cluster Randomization for Binary Outcomes 8 w0 v/ e. r: B& @- Z) k
Nonparametric Approach for One-Sample Clustered Binary Outcomes
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Sample Size Determination for Repeated Measurement Outcomes Using Summary Statistics
  x' w4 r5 }+ ^4 L3 q$ B) Q' lIntroduction 5 a: P( ~6 ^6 K* \. H0 y5 G
Information Needed for Sample Size Estimation
' S" S  ~& z' c" ?3 u) QSummary Statistics $ E3 r/ r: l0 U" `
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Sample Size Determination for Correlated Outcome Measurements Using GEE 2 Q2 }5 w# i- d
Motivation
& G% E. U) t/ o0 v+ O7 pReview of GEE
" F! {  V) d0 _% xCompare the Slope for a Continuous Outcome ! ~3 ]( Z* E- u2 M
Test the TAD for a Continuous Outcome % l! [5 b9 q6 i8 u1 t/ r% e
Compare the Slope for a Binary Outcome
5 a; N0 @& Q7 n2 u6 @' WTest the TAD for a Binary Outcome 3 S. o, u7 W: d# Y' W5 z8 R. J
Compare the Slope for a Count Outcome
/ E9 B1 R9 }+ E1 O6 y5 x: RTest the TAD for a Count Outcome
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Sample Size Determination for Correlated Outcomes from Two-Level Randomized Clinical Trials
8 G2 J; ~! y) A  g; {& n" AIntroduction
" z' T( z- E3 @3 L: t. _Statistical Models for Continuous Outcomes 1 J* P$ x! o0 v  b7 E
Testing Main Effects 0 e8 s' L4 Q* ?" `) M4 n
Two Level Longitudinal Designs: Testing Slope Differences
" l8 d, Q! p; k& `2 |1 tCross-Sectional Factorial Designs: Interactions between Treatments 6 b/ ^8 T) w. W
Longitudinal Factorial Designs: Treatment Effects on Slopes
& z! {4 n+ Z7 N0 m2 e/ P" oSample Sizes for Binary Outcomes   w) w2 V/ k- ]! b4 U+ W" W8 e
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* h9 p& R: t( ]* \8 S7 ESample Size Determination for Correlated Outcomes from Three Level Randomized Clinical Trials
# \, q6 }( I0 b5 e* LIntroduction ' T4 S) I. A5 U8 J1 p
Statistical Model for Continuous Outcomes ( e' K4 T0 Q2 Q* E8 ]1 T; x7 G7 U
Testing Main Effects
. `7 X( N# |. I. O" p8 v. ]7 uTesting Slope Differences
0 I+ _; y& z) I8 s. {9 N8 d5 fCross-Sectional Factorial Designs: Interactions between Treatments   T- X2 Z1 W* A1 y$ R: `
Longitudinal Factorial Designs: Treatment Effects on Slopes
  V8 }7 o8 n# X3 {4 w, d' bSample Sizes for Binary Outcomes
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Further Readings appear at the end of each chapter.
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 楼主| epiman 发表于 2015-10-12 15:34:00 | 显示全部楼层
Author(s) Bio- r/ Y" h  m: ^1 Y' ]6 F

+ E1 N! z- s# FChul Ahn, PhD, is a professor in the Department of Clinical Sciences and the cancer center associate director for biostatistics and bioinformatics in the Simmons Comprehensive Cancer Center at the University of Texas Southwestern Medical Center. He is also director of Biostatistics and Research Design for the NIH-sponsored Clinical and Translational Science Award (CTSA). He has published more than 370 peer-reviewed papers addressing the design and analysis of clinical trials and epidemiological studies as well as the evaluation of repeated measurements and correlated data.
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Moonseong Heo, PhD, is a professor in the Department of Epidemiology & Population Health at the Albert Einstein College of Medicine. His research includes sample size determinations for clinical trials, meta-analysis, longitudinal data analysis applying mixed-effects models, handling attrition problems in clinical trials data, and epidemiology in the fields of obesity and psychiatry.
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Song Zhang, PhD, is an associate professor in the Department of Clinical Sciences at the University of Texas Southwestern Medical Center. He has extensive experience in the design of clinical trials with correlated outcomes, addressing challenges that involve different correlation structures, missing data patterns, financial constraints, and historical controls. He is also interested in Bayesian statistical methods and their application in longitudinal and survival data analysis, high-throughput data analysis, disease mapping, adaptive design for clinical trials, and missing data imputation.
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jiran666 发表于 2018-1-19 10:04:22 | 显示全部楼层
请问有中文版吗
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