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[分享] [福利] 8本Meta分析英文原版电子书(免费PDF下载)

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sampson2010 发表于 2014-10-18 13:59:51 | 显示全部楼层 |阅读模式

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本帖最后由 sampson2010 于 2015-3-3 21:18 编辑
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Advances in Meta-Analysis+ Z, m/ t$ N: `' u; t  f: m2 X
dfb1ae72d031988dd5514bba6255e827-d.jpg
" `6 G  q# ~: {+ K5 L1 X4 ^Author(s):Terri D. Pigott
# o4 M' k- n% G/ O+ D1 |7 ISeries: Statistics for Social and Behavioral Sciences) r8 ^9 ~% i, Y5 Q8 b
Publisher: Springer6 S/ |7 A! ?7 h+ W; t1 F  B5 b( P6 x. W; k
Year: 2012        * g8 A9 C- ?' A* ]4 H' w* W+ l
Edition: 2012
" u6 J# T- D2 x9 \5 DLanguage: English        / p9 }6 k/ T; m/ u  s
Pages: 170
( ]" [& b  H2 |5 S2 j

5 f5 c1 X2 z3 x( N0 x! G2 ^Table of contents : % v4 @- h) t/ e# z1 A/ O$ ?7 y
Cover......Page 1
" b8 |; G8 ^" GStatistics for Social and Behavioral Sciences......Page 2
' T: B" h) a$ a# z; z$ S. |- ~Advances in Meta-Analysis......Page 4
4 B0 I2 v$ \, u2 JISBN 9781461422778......Page 5
5 |+ z: q& c* [Acknowledgements......Page 8/ T6 k. Q/ e/ m
Contents......Page 10' Z& C7 p2 e0 {) z' R: y
1.1 Background......Page 16, G. R+ M' [$ T' k- ~4 \# l
1.2 Planning a Systematic Review......Page 17) Z) }, w. n0 s- _4 i
1.4 Interpreting Results from a Meta-analysis......Page 19' T! }; g  {6 ]/ h
1.5 What Do Readers Need to Know to Use This Book?......Page 20
# z1 \! s  \2 w7 S* aReferences......Page 21
1 O9 g: s/ f- D+ G/ z* z2.2 Introduction to Notation and Basic Meta-analysis......Page 22
$ ]0 Q& c: @3 d9 a! o( J2.3 The Random Effects Mean and Variance......Page 230 x3 f# d6 _# [
2.4.2 Correlation Coefficient......Page 25
# U" J% r& R% [5 n: U6 U2.4.3 Log Odds Ratio......Page 26
0 o# ^/ \& E! H& z2 A1 U! S' DReferences......Page 27
4 ~) [/ Y# B; S+ f0 i% V3.1 Background......Page 28
: h- C/ y$ T& {3.2 Deciding on Important Moderators of Effect Size......Page 29
, P9 Z' j9 s1 z1 v$ ^: B0 d3.3 Choosing Among Fixed, Random and Mixed Effects Modelsƒ......Page 313 h% _  D0 j1 `, X1 B
3.4 Computing the Variance Component in Random and Mixed Models......Page 33
$ t& V2 d* F  B" u; d4 C3 g; S; W3.4.1 Example......Page 35
' Q( ]# L2 u4 O3.5 Confounding of Moderators in Effect Size Models......Page 36* O% E& o4 U/ G7 n% L9 h/ I* [
3.5.1 Example......Page 38" v. b- {0 R9 V2 P
3.6.1 Example......Page 40- c, L" K2 C' L/ n3 |
3.7 Interpretation of Moderator Analyses......Page 43
8 U3 U' f$ ]: I7 _Computing the Variance Component Using SAS......Page 446 @. E9 l5 H8 N7 [! k2 L* ?# [" ~
Computing the Variance Component Using R......Page 45. x' F  W/ C, Y' e
Computing the Fixed Effects Meta-regression Using SAS......Page 46. q) j% f% `# ?/ d# l
References......Page 473 c( {2 @" Q) F% O" q
4.1 Background......Page 50
+ H# S6 S  x: b" _9 D4.2 Fundamentals of Power Analysis......Page 52
, h+ @; U: C8 ]4 v! B4.3.1 Z-Test for the Mean Effect Size in the Fixed Effects Modelƒ......Page 546 g; J, Q) J& G5 ]
4.3.2 The Power of the Test of the Mean Effect Size in Fixed Effects Models......Page 56
+ p; \0 e# s9 }4 @4.3.3 Deciding on Values for Parameters to Compute Power......Page 57
5 G7 \" `8 m0 G% }4 i7 X8 [. w4.3.4 Example: Computing the Power of the Test of the Mean......Page 58
* X6 ~9 J( W( k/ h' }9 d3 ]# ]' p/ Y4.3.5 Example: Computing the Number of Studies Needed to Detect an Important Fixed Effects Mean......Page 60
; {7 D" U& S8 ]0 b9 [. a4.3.6 Example: Computing the Detectable Fixed Effects Mean in a Meta-analysis......Page 619 z1 q- G! i  F* T: K9 c' v
4.4 Test of the Mean Effect Size in the Random Effects Model......Page 62; s* X. s1 l8 O3 K' k, I
4.4.1 The Power of the Test of the Mean Effect Size in Random Effects Models......Page 63
" y& }2 V/ Y: g7 f/ d4.4.2 Positing a Value for tau2 for Power Computations in the Random Effects Model......Page 64
. p4 ]8 X. E5 |8 L# Q# a3 x, M4.4.3 Example: Estimating the Power of the Random Effects Mean......Page 65
9 y- g( N8 c: c7 a' ~. T6 U3 v4.4.4 Example: Computing the Number of Studies Needed to Detect an Important Random Effect Mean......Page 66
6 G- x. F3 a  V. _: y" SExcel......Page 67
, A# M& `; F' n9 E7 aReferences......Page 68. e3 G% Q8 ^: [; |" O/ W
5.1 Background......Page 702 H+ I" o0 ]9 [7 Y. l' e) f
5.2.1 The Power of the Test of Homogeneity in a Fixed Effects Model......Page 717 }1 o- n- O! E% R
5.2.2 Choosing Values for the Parameters Needed to Compute Power of the Homogeneity Test in Fixed Effects Models......Page 72) [1 e' _$ p1 n$ l9 [4 P; Y" r$ U
5.2.3 Example: Estimating the Power of the Test of Homogeneity in Fixed Effects Models......Page 73/ O- z8 ]4 r% }+ z5 S. Z6 m) i
5.3 The Test of the Significance of the Variance Component in Random Effects Models......Page 74
- V* _# W; Q9 T, \& t3 [- m' a5.3.1 Power of the Test of the Significance of the Variance Component in Random Effects Models......Page 75
2 T4 Y" X6 x1 m% E- U" J. {5.3.2 Choosing Values for the Parameters Needed to Compute the Variance Component in Random Effects Models......Page 76$ s9 `' h3 ], U; d2 q
5.3.3 Example: Computing Power for Values of tau2, the Variance Component......Page 77
$ M3 }( O8 ^, ]0 y% M* c  \; vSAS......Page 79
, H+ `' y% Y5 Z8 UR......Page 80
( |2 B  K& @' `References......Page 81' w8 c8 W# w  Y$ l7 n& z
6.1 Background......Page 82) K% U# Q' ^& Y, N1 ^, W2 j+ X
6.2.2 Power of the Test of Between-Group Homogeneity, QB, in Fixed Effects Models......Page 83) z( {$ t. e5 c8 O$ W
6.2.4 Example: Power of the Test of Between-Group Homogeneity in Fixed Effects Models......Page 85( X  z1 b6 Z3 m0 ?
6.2.5 Power of the Test of Within-Group Homogeneity, QW, in Fixed Effects Models......Page 868 f/ C) R' J6 U, Y" ]/ x) N9 w, e. b
6.2.6 Choosing Parameters for the Test of QW in Fixed Effects Models......Page 87
* c3 F4 g) H7 i( I& ]  B8 ?6.2.7 Example: Power of the Test of Within-Group Homogeneity in Fixed Effects Models......Page 88$ k# S$ T/ X, x, q" l8 O
6.3.1 Power of Test of Between-Group Homogeneity in the Random Effects Model......Page 89
* x0 {% E# q; ~9 m: V+ _6.3.3 Example: Power of the Test of Between-Group Homogeneity in Random Effects Models......Page 911 ]8 l3 f1 k; i  p4 z
References......Page 93
' Y& [; w$ X; K# t  ?7.1 Background......Page 94
& d! Z' p: w7 e( `; P7 P( O# m7.2.1 Identification of Publication Bias......Page 95/ W4 s, d: X1 r8 A# o" W# ?
7.2.1.1 Example of Funnel Plot......Page 96& `+ U* F7 F3 X# M1 f
7.2.2 Assessing the Sensitivity of Results to Publication Bias......Page 97' m$ S# N  U! N; Y7 s" A; ~
7.3 Missing Effect Sizes in a Meta-analysis......Page 1003 B" g3 t. T( b  A8 G
7.4 Missing Moderators in Effect Size Models......Page 101
2 D! k2 n# w  P0 X! `3 G* ?7.5 Theoretical Basis for Missing Data Methods......Page 102
' g! `2 e& q, f$ i7.5.1 Multivariate Normality in Meta-analysis......Page 103. d5 y% G% J( U, t+ T
7.5.2 Missing Data Mechanisms or Reasons for Missing Data......Page 104) ^9 `1 f. p* n9 ~) R+ A  T
7.6.1 Complete-Case Analysis......Page 105! N! `3 u: v2 h! W; O' P+ D8 ]% ~
7.6.1.1 Example: Complete-Case Analysis......Page 106" J4 Z+ ^+ @9 @
7.6.2 Available Case Analysis or Pairwise Deletion......Page 107
. ^6 _8 c* K6 [" C) f7.6.3 Single Value Imputation with the Complete Case Mean......Page 1085 I$ L3 Y$ `) r6 U  U# g
7.6.3.1 Example: Mean Imputation......Page 109
! u7 S4 j# w6 o/ S7.6.4 Single Value Imputation Using Regression Techniques......Page 110) i5 v& n) |" U+ r4 W0 U3 o
7.6.4.1 Example: Regression Imputation......Page 111
: c7 [, q  ~  L* T) p& [9 q/ s7.7.1 Maximum-Likelihood Methods for Missing Data Using the EM Algorithm......Page 112. q+ L* |! h: D6 J# r
7.7.1.1 Example Using the EM Algorithm......Page 113& D  F# C- P0 P" ~# a8 s
7.7.2.1 Generating Multiple Imputations......Page 1145 }5 s# b3 n- a, d6 S
7.7.2.3 Combining the Estimates......Page 115/ Z, |$ h9 l7 q$ X6 ?
R Programs......Page 117
! b- y; _4 M1 ~SAS Proc MI......Page 119
! I' l8 ^9 }/ J1 _* P; ~7 _: F" n) m& cReferences......Page 121
1 W0 }& l) n( V& o. F. h$ x8.1 Background......Page 124
/ O: Y1 T  }* m/ L8.2 The Potential for IPD Meta-analysis......Page 125/ \6 h! s" o( X# ]# Y: l: Z% g
8.3.1 Simple Random Effects Models with Aggregated Data......Page 127$ [. H6 n: R8 @1 {; ?- }
8.3.2.1 Example: Two-Stage Method Using Correlation as the Effect Size......Page 129
2 T6 K8 z- `; O% L$ z3 p6 ^8.4.1 IPD Model for the Standardized Mean Difference......Page 1301 a+ F( W. Z# C5 ?* o9 ?5 O6 N
8.4.3 Model for the One-Stage Method with Both IPD and AD......Page 131
3 u. V4 g! O6 {4 J& t; N' }8.5 Effect Size Models with Moderators Using a Mix of IPD and AD......Page 133  O" {/ k2 ~' o' r
8.5.1 Two-Stage Methods for Meta-regression with a Mix of IPD and AD......Page 1343 F. |$ f1 w# _5 K0 x
8.5.2 One-Stage Method for Meta-regression with a Mix of IPD and AD......Page 135+ }/ g9 c4 ?: o) F$ J7 Z$ b8 L
8.5.4 One-Stage Meta-regression with a Mix of IPD and AD......Page 136: V2 f5 ?* _  I' Y
8.5.4.1 Example: One-Stage Method for Meta-regression with Correlationsƒ......Page 137
0 o3 p9 ]/ v. R6 K: [3 Q2 DSAS Code for Simple Random Effects Model Using the Two-Step Method......Page 138
/ ~1 E% {0 q! \. dOutput from Two-Stage Simple Random Effects Model......Page 139; s# z; o, q+ t1 j1 ^
SAS Code for Meta-regression Using the Two-Stage Method......Page 140
# d. g; _0 o% z) a* Z& ~. KSAS Code for Simple Random Effects Model Using the One-Stage Model......Page 141
* h+ P# k& a* N) K6 u9 nOutput from One-Stage Simple Random Effects Model......Page 143
& I; h  C" \6 vOutput for Meta-regression Using the One-Step Method......Page 144% |' n  m! L) o6 q; C3 X
References......Page 145
- ]& b+ W& K) E. h9.1 Background......Page 148
# [# m+ j. r3 Q: ^% O4 g) a9.1.1 The Preventive Health Services (2009) Report on Breast Cancer Screening......Page 149- y+ ^4 y. M( b5 [; B& R1 [
9.2.1 Surface Similarity......Page 150! }$ P! x0 F$ r9 n9 }) B2 C
9.2.2 Ruling Out Irrelevancies......Page 151: e/ s, _' q8 |; X
9.2.3 Making Discriminations......Page 152
7 [* D# [  e. Z& Y9.2.5 Causal Explanation......Page 153, H/ o- \  z6 Q# j5 ?
9.3 Suggestions for Generalizing from a Meta-analysis......Page 154! ^! G" c/ M& @8 s+ h$ B) Y1 b
References......Page 155# ]) [( r  B" a6 G9 m6 I
10.2 Understanding the Research Problem......Page 1586 q9 ?1 ]8 r% x* K
10.3 Having an a Priori Plan for the Meta-analysis......Page 1599 p; D% m  g6 h8 j3 Y0 ~& D9 g
10.4 Carefully and Thoroughly Interpret the Results of Meta-analysis......Page 160! [2 k! ]2 W( C9 M
References......Page 1618 U; H+ I$ }- {. b
11.1 Sirin (2005) Meta-analysis on the Association Between Measures of Socioeconomic Status and Academic Achievement......Page 1627 c. l' h. g4 e( p  g
11.2 Hackshaw et al. (1997) Meta-analysis on Exposure to Passive Smoking and Lung Cancer......Page 164
& b/ J$ C+ M9 }1 {; K4 e( f11.3 Eagly et al. (2003) Meta-analysis on Gender Differences in Transformational Leadership......Page 166, @8 ~( R# d( X. @8 u, K- K
References......Page 167* b* G; V0 C' ~7 L: y+ u3 Q: G
Index......Page 168& h! n% V& _/ l. l! j7 ~
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猫猫咪吖 发表于 2015-3-15 21:23:02 | 显示全部楼层
看不懂!
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糊涂毛毛虫 发表于 2015-3-19 15:06:57 | 显示全部楼层
谢谢楼主!!!!非常棒的资料~!
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zx08192004 发表于 2015-5-6 13:30:37 | 显示全部楼层
超级有用的资料,感谢楼主的分享,真得好好的学习学习。
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txyw 发表于 2015-5-11 15:21:07 | 显示全部楼层
楼主牛逼,有没有关于网络meta的书啊
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insect16 发表于 2015-6-26 11:25:52 | 显示全部楼层
感谢楼主无私分享
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MLJ要奋斗 发表于 2015-7-2 10:16:30 | 显示全部楼层
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 楼主| sampson2010 发表于 2015-7-2 15:29:39 | 显示全部楼层
txyw 发表于 2015-5-11 15:21& a- I6 f: W* d) Q; q2 ^; \/ X: Q
楼主牛逼,有没有关于网络meta的书啊
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最近忙于毕业,没时间整理,等闲下来了再发帖,记得关注哦!
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fisher163 发表于 2015-8-14 20:13:31 | 显示全部楼层
可以点个赞
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山脚下的小姑娘 发表于 2015-8-21 16:56:01 | 显示全部楼层
楼主太厉害了,非常感谢楼主的无私分享。向楼主学习。
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