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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 ' H; o. Z2 C8 U
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Advances in Meta-Analysis
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* B  a2 r5 P" V1 S0 TAuthor(s):Terri D. Pigott$ I7 y& @( q- Y" H( j1 c1 a
Series: Statistics for Social and Behavioral Sciences* |' }* o' M: J
Publisher: Springer
" v. m7 b" B& i9 b3 `Year: 2012        + z- a& A9 t( T! A
Edition: 2012
1 Z2 G; e! U$ Q; A8 q( |6 nLanguage: English       
/ v$ }5 l6 z- A# o. V; \, IPages: 170
" K: @/ m6 \  S, ?9 j6 h: L
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Table of contents : . ~4 ]3 d# T% T/ `  y
Cover......Page 18 g0 C, j: h7 I9 P" o- u
Statistics for Social and Behavioral Sciences......Page 2  p# ~: y( L. H' W; R9 _
Advances in Meta-Analysis......Page 4  y$ h$ Y: E: w9 e
ISBN 9781461422778......Page 5* G  a5 T1 H" \2 R. n2 H
Acknowledgements......Page 8
7 v/ l- }% _5 K; C5 j. \" b% s& SContents......Page 10" A3 |5 A+ C8 N2 R
1.1 Background......Page 16
$ l+ ^& a1 G* I+ o1.2 Planning a Systematic Review......Page 17
8 E& t, E" ^8 s2 S. x1.4 Interpreting Results from a Meta-analysis......Page 19
# V' G7 ^% t- w; V- P9 s# _1.5 What Do Readers Need to Know to Use This Book?......Page 20
5 Z4 i/ B- d! n, f0 N; }% tReferences......Page 21) _' o/ f9 q8 Y0 F
2.2 Introduction to Notation and Basic Meta-analysis......Page 220 F9 d0 p7 M: K+ v
2.3 The Random Effects Mean and Variance......Page 23
  `) a9 r. T! I9 d5 M. U9 m2.4.2 Correlation Coefficient......Page 25' y& S! o- Q9 d$ k
2.4.3 Log Odds Ratio......Page 26
, C1 S1 {* c/ w" y8 CReferences......Page 274 i# ^/ ~+ r2 E: M# C. S
3.1 Background......Page 282 K& B5 K; N; ~1 s$ m8 m% _3 P
3.2 Deciding on Important Moderators of Effect Size......Page 29" \+ J& z0 Y3 R6 {  D) k: g
3.3 Choosing Among Fixed, Random and Mixed Effects Modelsƒ......Page 31
) j1 w0 @5 w: C0 @8 Y3.4 Computing the Variance Component in Random and Mixed Models......Page 33: S& ~, Y$ Q0 ]0 z/ `9 T+ M4 X) g
3.4.1 Example......Page 359 ^, S' R9 _* F% @& A6 k
3.5 Confounding of Moderators in Effect Size Models......Page 368 P' c! p: l5 \6 O& r
3.5.1 Example......Page 38
! {% @3 A3 M1 ?2 Y, z! @3.6.1 Example......Page 40
. O: M2 P8 s! E% G9 ~# b* m$ l3.7 Interpretation of Moderator Analyses......Page 43
" ]4 q' ^5 f* l* f1 R  IComputing the Variance Component Using SAS......Page 44
% I4 [/ F. ]9 W- Y" qComputing the Variance Component Using R......Page 45
9 a0 p: ^9 G: r+ }2 AComputing the Fixed Effects Meta-regression Using SAS......Page 46# C" f& m) w, v* z, F
References......Page 47
3 x: G( G. V( C- G4.1 Background......Page 50* H. j8 O- ~* d" w! a3 i. o. X( s
4.2 Fundamentals of Power Analysis......Page 52
; U7 ^/ ~2 A* m4.3.1 Z-Test for the Mean Effect Size in the Fixed Effects Modelƒ......Page 54
2 D3 ~7 L* ]# w. S4.3.2 The Power of the Test of the Mean Effect Size in Fixed Effects Models......Page 56' @, x6 ]) @7 I3 h& h
4.3.3 Deciding on Values for Parameters to Compute Power......Page 57% ]$ O; n) R9 S5 V
4.3.4 Example: Computing the Power of the Test of the Mean......Page 58
1 [$ j, c" n9 N4.3.5 Example: Computing the Number of Studies Needed to Detect an Important Fixed Effects Mean......Page 60! l3 M% |/ G1 T; N
4.3.6 Example: Computing the Detectable Fixed Effects Mean in a Meta-analysis......Page 616 c7 J8 o( h' m" h" m1 ^! R
4.4 Test of the Mean Effect Size in the Random Effects Model......Page 62
2 t- L0 r: X1 O/ s8 y* |5 F) X) X4.4.1 The Power of the Test of the Mean Effect Size in Random Effects Models......Page 63
4 `+ t6 P! ?' T3 K  ^9 i4.4.2 Positing a Value for tau2 for Power Computations in the Random Effects Model......Page 64
. N& D. h3 C' I9 V4 C1 J4.4.3 Example: Estimating the Power of the Random Effects Mean......Page 65! l, z$ e. P( w2 H. Z
4.4.4 Example: Computing the Number of Studies Needed to Detect an Important Random Effect Mean......Page 66, e0 B% O! H) B! ]4 ]/ w" W
Excel......Page 67
7 |" [6 H+ |/ t/ v! z  q& k3 |( GReferences......Page 68
; {* y. y3 v" m& ?5.1 Background......Page 70! t& w* n9 i6 d  X4 L
5.2.1 The Power of the Test of Homogeneity in a Fixed Effects Model......Page 71
; q5 s5 b# v# H, k5.2.2 Choosing Values for the Parameters Needed to Compute Power of the Homogeneity Test in Fixed Effects Models......Page 72
0 }) ?0 u6 F- @5.2.3 Example: Estimating the Power of the Test of Homogeneity in Fixed Effects Models......Page 73
  H) {% w5 p0 i9 X5.3 The Test of the Significance of the Variance Component in Random Effects Models......Page 746 q5 W' k9 A# B/ B: g5 }
5.3.1 Power of the Test of the Significance of the Variance Component in Random Effects Models......Page 753 C; a( ~( B6 g
5.3.2 Choosing Values for the Parameters Needed to Compute the Variance Component in Random Effects Models......Page 762 L  @  n! H, L) |- s% ]# _8 N
5.3.3 Example: Computing Power for Values of tau2, the Variance Component......Page 77
6 ^$ c5 W5 F9 F3 xSAS......Page 79
, Z) J/ z) |/ [7 B! p3 L7 {R......Page 80
! w7 Y6 M: G" S! G2 jReferences......Page 81
/ d5 }; Z# C  o* ?4 g0 s: J9 d6.1 Background......Page 82, G; U+ g; K2 J! b
6.2.2 Power of the Test of Between-Group Homogeneity, QB, in Fixed Effects Models......Page 83$ Q/ J4 O' O7 B1 g6 {
6.2.4 Example: Power of the Test of Between-Group Homogeneity in Fixed Effects Models......Page 85% E7 n6 n+ G. o# o1 W3 z
6.2.5 Power of the Test of Within-Group Homogeneity, QW, in Fixed Effects Models......Page 86
$ w; v+ _8 ^, ~# }% a5 o6.2.6 Choosing Parameters for the Test of QW in Fixed Effects Models......Page 87
1 T6 ]8 j7 _$ X- H' f% e' }6.2.7 Example: Power of the Test of Within-Group Homogeneity in Fixed Effects Models......Page 88
+ ^: s  d6 M8 T! b6.3.1 Power of Test of Between-Group Homogeneity in the Random Effects Model......Page 890 |9 G% }" R- s' D6 G5 u
6.3.3 Example: Power of the Test of Between-Group Homogeneity in Random Effects Models......Page 91
. B* R) G$ h% kReferences......Page 93* k9 U+ |( C& n( l
7.1 Background......Page 94
0 j' u1 c' H: d% J7.2.1 Identification of Publication Bias......Page 95
6 |9 j8 X2 F. |3 d3 u7 _$ ^7.2.1.1 Example of Funnel Plot......Page 96$ U" l* ~2 Q. j9 I' K
7.2.2 Assessing the Sensitivity of Results to Publication Bias......Page 97
" R$ U5 C* |9 h& J7 |* _& P7.3 Missing Effect Sizes in a Meta-analysis......Page 100
/ z8 Q/ j9 K; u7.4 Missing Moderators in Effect Size Models......Page 101
' c# R5 J7 G1 `( Y4 R7.5 Theoretical Basis for Missing Data Methods......Page 102
' m  x/ g- T2 k& h+ ~5 p& @7.5.1 Multivariate Normality in Meta-analysis......Page 103
/ |! r( a4 B) \: M; r7.5.2 Missing Data Mechanisms or Reasons for Missing Data......Page 104
' H" R# [" ~0 }7.6.1 Complete-Case Analysis......Page 105
3 i( d) Q* E5 Y5 X7.6.1.1 Example: Complete-Case Analysis......Page 1065 t  p" c  r- U3 t8 U) C
7.6.2 Available Case Analysis or Pairwise Deletion......Page 107" H5 w( L, t/ o$ f) O1 ], |
7.6.3 Single Value Imputation with the Complete Case Mean......Page 108
" m2 P) m8 Q0 j& Z* U7.6.3.1 Example: Mean Imputation......Page 109
: a5 A. P3 s! m0 q* b7.6.4 Single Value Imputation Using Regression Techniques......Page 110
" y4 G$ t, V4 ]" X% p0 K. x# P7.6.4.1 Example: Regression Imputation......Page 111* g8 v/ |0 o, w: X4 w
7.7.1 Maximum-Likelihood Methods for Missing Data Using the EM Algorithm......Page 112
- J7 i1 r7 E, p+ R0 h4 @7.7.1.1 Example Using the EM Algorithm......Page 113" h3 p4 e9 s3 D& C+ a  u: A
7.7.2.1 Generating Multiple Imputations......Page 1149 @% w/ I5 q# b1 E6 F  ~+ A
7.7.2.3 Combining the Estimates......Page 115. s2 S( i) G6 M8 j0 `8 e
R Programs......Page 117
& S( _# S/ X2 [  N( MSAS Proc MI......Page 119
8 O2 s+ a. f. M$ {References......Page 121
$ f8 f3 I3 [6 ]% v( Q! ^& X! K/ F4 J8.1 Background......Page 124
* F$ G8 n- H0 d7 [/ W9 L, o8.2 The Potential for IPD Meta-analysis......Page 125% {7 x$ K! l0 X& `) d  F, P5 ~
8.3.1 Simple Random Effects Models with Aggregated Data......Page 127
$ w8 Y9 N7 G1 }. u7 L- X9 l8.3.2.1 Example: Two-Stage Method Using Correlation as the Effect Size......Page 129
; U0 b9 U  s/ @9 Q8 M8.4.1 IPD Model for the Standardized Mean Difference......Page 130+ Q: R% O- N( g4 O  F# g; i9 `
8.4.3 Model for the One-Stage Method with Both IPD and AD......Page 131
5 ]+ _. s  D6 u! D7 b( F" Q8.5 Effect Size Models with Moderators Using a Mix of IPD and AD......Page 133
5 v7 o6 l; Z& C5 g: ]+ l5 ], j8.5.1 Two-Stage Methods for Meta-regression with a Mix of IPD and AD......Page 134, |" _( D5 @8 A" o) O- R
8.5.2 One-Stage Method for Meta-regression with a Mix of IPD and AD......Page 135
6 o. |. W9 y% M0 ?) p8.5.4 One-Stage Meta-regression with a Mix of IPD and AD......Page 136
8 Y2 t" d9 G7 B2 a7 h8.5.4.1 Example: One-Stage Method for Meta-regression with Correlationsƒ......Page 1376 z4 v* G* q9 u7 T6 D
SAS Code for Simple Random Effects Model Using the Two-Step Method......Page 138# _/ U  q3 ?8 o- q+ I7 j6 D/ a$ X
Output from Two-Stage Simple Random Effects Model......Page 139
) S+ D( m, P2 a7 y- |+ TSAS Code for Meta-regression Using the Two-Stage Method......Page 140
8 @" U) k9 m  A! `" d( x) I" HSAS Code for Simple Random Effects Model Using the One-Stage Model......Page 141
6 y2 E' w. t+ c6 @Output from One-Stage Simple Random Effects Model......Page 143
8 ^9 d2 G4 F0 o$ Z0 UOutput for Meta-regression Using the One-Step Method......Page 144$ a/ R9 ]% D; @% R  s/ J
References......Page 145
2 {# d: E' R( H9.1 Background......Page 1489 Q4 |) }+ ]9 F' L2 a, Z& g
9.1.1 The Preventive Health Services (2009) Report on Breast Cancer Screening......Page 149
6 V( u0 s; k" ]1 z) j+ V) h4 e  F9.2.1 Surface Similarity......Page 150+ @( r: P( J( W! \- j0 ]; x! U
9.2.2 Ruling Out Irrelevancies......Page 151
5 q% k& ~* }1 R, J& c* P3 N9.2.3 Making Discriminations......Page 152. D( N" H3 o7 J( r
9.2.5 Causal Explanation......Page 153
/ K7 L( W# L$ O9.3 Suggestions for Generalizing from a Meta-analysis......Page 154
9 w4 M& u. m: H: |$ V  s$ EReferences......Page 1554 J* `; A# i: s2 T6 j* x
10.2 Understanding the Research Problem......Page 158# l; n$ a8 |! d% i+ O. ~
10.3 Having an a Priori Plan for the Meta-analysis......Page 159
4 s0 L3 a" s" w( T5 z' u10.4 Carefully and Thoroughly Interpret the Results of Meta-analysis......Page 160
6 Y3 m$ F5 p" F' FReferences......Page 161
7 ^  T5 K$ k4 U7 X- ?/ \: ~5 @11.1 Sirin (2005) Meta-analysis on the Association Between Measures of Socioeconomic Status and Academic Achievement......Page 162& a" }6 f: E+ v
11.2 Hackshaw et al. (1997) Meta-analysis on Exposure to Passive Smoking and Lung Cancer......Page 164
/ e# m$ @. e- M! B& ^11.3 Eagly et al. (2003) Meta-analysis on Gender Differences in Transformational Leadership......Page 166/ \6 M2 a! S5 |* f6 j) z) c
References......Page 167
! I% x$ }3 F/ Z! P) |3 j% W; AIndex......Page 168
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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% q1 O6 t- \3 O8 z9 I
楼主牛逼,有没有关于网络meta的书啊

% ]# G& M& E$ h- {; T" N: P3 w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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