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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 1 m, b4 |: S9 ?9 X  ~* A- P+ a

  b8 H! C0 @" _+ {, SAdvances in Meta-Analysis
  D* B# ]  y, w. ^, P dfb1ae72d031988dd5514bba6255e827-d.jpg 7 z: Z' V: D5 p% V
Author(s):Terri D. Pigott
* j0 Z$ Q8 `+ N( ?. eSeries: Statistics for Social and Behavioral Sciences
8 `4 W% t( J  J  o) ?- N4 IPublisher: Springer
/ |$ m, g0 L% h+ r, YYear: 2012       
- I) R( v6 F! A7 C8 V" Y7 k6 AEdition: 2012
- c% f0 r. V, a' b2 fLanguage: English       
. E) P4 w8 ]# D6 h& r; `7 e! A. }Pages: 170

: c! Q/ A' Y7 ~! h2 N# W1 R! ]+ a( c4 P5 R1 t% \1 R
Table of contents : 3 u( Q5 ~( J1 w: ]
Cover......Page 1( `0 C% ^2 H6 @: ]# B& Q
Statistics for Social and Behavioral Sciences......Page 23 a+ s' M- i6 z) i  ^
Advances in Meta-Analysis......Page 4
# {$ q) c" P8 ^6 l1 C' pISBN 9781461422778......Page 56 L$ a) c! C+ B" ]5 |4 i
Acknowledgements......Page 8
3 F, J, d; _1 g% C7 `# D& X! e" yContents......Page 100 M' p! j' M  K! i$ J  F. y
1.1 Background......Page 16  l5 L; c" j$ g. K9 }: H
1.2 Planning a Systematic Review......Page 17
  F; v' x: d3 u' r1.4 Interpreting Results from a Meta-analysis......Page 19
% ~# D! o& |$ y; X1.5 What Do Readers Need to Know to Use This Book?......Page 20
1 w3 F- |0 {" s) N: o& Z, Q3 rReferences......Page 21
& i9 ]6 o: a  B2.2 Introduction to Notation and Basic Meta-analysis......Page 220 ]9 `4 X, ]9 W7 q6 \. \
2.3 The Random Effects Mean and Variance......Page 23
1 q$ N" S6 l) `5 j) C2.4.2 Correlation Coefficient......Page 25
6 K; F/ E- n: Y2 e5 H2.4.3 Log Odds Ratio......Page 26
7 X5 G0 i/ t; @! F# ^2 pReferences......Page 27: S& T% b8 {3 x! C9 N
3.1 Background......Page 28
8 v% X) A( H# s9 f6 X6 j# w! o3.2 Deciding on Important Moderators of Effect Size......Page 29; R! G, z7 x9 X; i$ t1 g
3.3 Choosing Among Fixed, Random and Mixed Effects Modelsƒ......Page 310 v0 Q5 o3 \8 q' M: P7 }
3.4 Computing the Variance Component in Random and Mixed Models......Page 333 {& ?9 y* @* J2 f
3.4.1 Example......Page 35# X- W% a: e& n! |7 `4 j6 N8 P
3.5 Confounding of Moderators in Effect Size Models......Page 361 m' D* r" z2 g; n- p/ Z. m% D' l
3.5.1 Example......Page 387 T1 C( R3 A, ?9 {
3.6.1 Example......Page 405 [7 X7 E& s# L* `; D
3.7 Interpretation of Moderator Analyses......Page 431 r$ x8 u  Y6 O7 \8 ~+ q2 z
Computing the Variance Component Using SAS......Page 44
  n' F3 z. a  d/ d3 WComputing the Variance Component Using R......Page 45
% K9 R5 i  R+ m0 g) wComputing the Fixed Effects Meta-regression Using SAS......Page 46+ j; B  P) J; [1 n2 A9 Y
References......Page 47) o9 m; u. L: ?4 x1 P! L
4.1 Background......Page 50. h6 x% Y: a% ?+ j
4.2 Fundamentals of Power Analysis......Page 52
) _) \/ U0 x; k4 u$ A4.3.1 Z-Test for the Mean Effect Size in the Fixed Effects Modelƒ......Page 54
5 ~( w' w& n  z5 S4.3.2 The Power of the Test of the Mean Effect Size in Fixed Effects Models......Page 56
% z+ I# K' S- Z) d7 O8 s2 c4.3.3 Deciding on Values for Parameters to Compute Power......Page 57
, h. J4 J* z7 {/ k, U5 E% y/ b/ ~4.3.4 Example: Computing the Power of the Test of the Mean......Page 58
  Q& Z1 j, W8 g7 J/ D! W; a6 S5 T( P4.3.5 Example: Computing the Number of Studies Needed to Detect an Important Fixed Effects Mean......Page 60
/ Q( Z" W; j1 O8 U/ h) e4.3.6 Example: Computing the Detectable Fixed Effects Mean in a Meta-analysis......Page 61
% |4 E4 a8 p& X, ~! [- J+ p: a2 ]4.4 Test of the Mean Effect Size in the Random Effects Model......Page 62% y4 P& |& L3 A6 `( q
4.4.1 The Power of the Test of the Mean Effect Size in Random Effects Models......Page 63, D" ]  s) s* H( I
4.4.2 Positing a Value for tau2 for Power Computations in the Random Effects Model......Page 64
2 j+ j5 ^# P- S7 g& b# ]1 x4.4.3 Example: Estimating the Power of the Random Effects Mean......Page 65( W4 I7 H/ R+ q8 H5 H8 Y) Q
4.4.4 Example: Computing the Number of Studies Needed to Detect an Important Random Effect Mean......Page 66( P! f6 `/ _4 [& m
Excel......Page 67# |+ I0 z& j3 X8 D9 n" |% O
References......Page 687 V/ o) Y) O1 M$ b  s6 |0 q
5.1 Background......Page 70
' U, T/ x7 w+ M0 P5.2.1 The Power of the Test of Homogeneity in a Fixed Effects Model......Page 71
% P1 z0 P9 ^; M! |5.2.2 Choosing Values for the Parameters Needed to Compute Power of the Homogeneity Test in Fixed Effects Models......Page 727 @  m# f. V7 s# v) T( b% u
5.2.3 Example: Estimating the Power of the Test of Homogeneity in Fixed Effects Models......Page 73( ]* g+ T  t% B7 m, H; i- w
5.3 The Test of the Significance of the Variance Component in Random Effects Models......Page 745 C/ Y& @8 Y. G
5.3.1 Power of the Test of the Significance of the Variance Component in Random Effects Models......Page 75
2 |' u: E) d$ ~3 n/ {/ |$ S4 U* K6 k- E5.3.2 Choosing Values for the Parameters Needed to Compute the Variance Component in Random Effects Models......Page 76' _; b1 _$ ~, q
5.3.3 Example: Computing Power for Values of tau2, the Variance Component......Page 77% i  C# w9 V( n+ U
SAS......Page 79
% s( K3 _: J4 ]R......Page 80
: b  a& F/ \. f) z7 P# PReferences......Page 81+ {3 F- e) X$ T& b
6.1 Background......Page 82( w! V# D7 b! o9 b+ [, }
6.2.2 Power of the Test of Between-Group Homogeneity, QB, in Fixed Effects Models......Page 83
/ W: o; t5 ^6 R4 X6.2.4 Example: Power of the Test of Between-Group Homogeneity in Fixed Effects Models......Page 85
& z" M% ~8 a) n. W6.2.5 Power of the Test of Within-Group Homogeneity, QW, in Fixed Effects Models......Page 86
  u0 ^- C' x. v; ?5 C3 d6.2.6 Choosing Parameters for the Test of QW in Fixed Effects Models......Page 87' W4 t, b! I' u) S
6.2.7 Example: Power of the Test of Within-Group Homogeneity in Fixed Effects Models......Page 88
' g  S# w# F7 R" V6.3.1 Power of Test of Between-Group Homogeneity in the Random Effects Model......Page 89
9 O1 L" J/ m7 U  t& V) C6.3.3 Example: Power of the Test of Between-Group Homogeneity in Random Effects Models......Page 91/ B' j9 N) x! S; }/ p
References......Page 93
: m( ?$ |4 m# z" U1 \8 t9 b7.1 Background......Page 94
1 P" r1 b* C" E. B9 C' \) ^# \7.2.1 Identification of Publication Bias......Page 95" [: j7 p9 y- g# i( g5 X
7.2.1.1 Example of Funnel Plot......Page 96
) {6 u- k/ t% F$ t, e5 u7.2.2 Assessing the Sensitivity of Results to Publication Bias......Page 97
0 V  j; A* b; I1 D5 I9 g7.3 Missing Effect Sizes in a Meta-analysis......Page 1003 A% E) w' i) Z
7.4 Missing Moderators in Effect Size Models......Page 101
$ [+ ^/ B6 ~8 j  r+ B2 H7.5 Theoretical Basis for Missing Data Methods......Page 102* B# h  J& t5 j4 ^% f
7.5.1 Multivariate Normality in Meta-analysis......Page 103& x- ^* b) `2 d7 i' u
7.5.2 Missing Data Mechanisms or Reasons for Missing Data......Page 104
0 O" U( e' Q- {7.6.1 Complete-Case Analysis......Page 105
& W; |% _' }3 w# w; q6 U7.6.1.1 Example: Complete-Case Analysis......Page 106
- p6 E0 P0 K2 c  W) Y7 y+ \7.6.2 Available Case Analysis or Pairwise Deletion......Page 107
4 b7 w0 l: x& {. O7.6.3 Single Value Imputation with the Complete Case Mean......Page 108, _! G) g9 P- k: D7 j9 X
7.6.3.1 Example: Mean Imputation......Page 109
2 D9 ^( R% G& c' H7.6.4 Single Value Imputation Using Regression Techniques......Page 110
2 Y( I0 j+ u( s/ r7.6.4.1 Example: Regression Imputation......Page 111/ D" a: \1 A- j, f
7.7.1 Maximum-Likelihood Methods for Missing Data Using the EM Algorithm......Page 112
4 P6 l: h9 g+ H5 |7.7.1.1 Example Using the EM Algorithm......Page 113
2 }# ?& {5 p0 x- e6 K1 m7.7.2.1 Generating Multiple Imputations......Page 114
# Q( O2 o* m3 Y1 ^7.7.2.3 Combining the Estimates......Page 115% ~! M' H! s' m1 {! s
R Programs......Page 117
  u' ?% x  z' \! T3 J8 HSAS Proc MI......Page 119
: }+ m6 e% S. r5 u& xReferences......Page 121
! L; [$ c; s4 p* v0 V8.1 Background......Page 1241 c1 d! W8 x  _9 Z, t& y, Q
8.2 The Potential for IPD Meta-analysis......Page 125
  j) e9 C) ~% A4 b, H8.3.1 Simple Random Effects Models with Aggregated Data......Page 127
1 B# y9 X) Q% O+ ?  ^" b8.3.2.1 Example: Two-Stage Method Using Correlation as the Effect Size......Page 129
6 f. b1 S2 J( }$ E" ~6 L& w" u7 J8.4.1 IPD Model for the Standardized Mean Difference......Page 130. k9 ~  O0 e1 ?# b# F
8.4.3 Model for the One-Stage Method with Both IPD and AD......Page 1317 Y7 B1 x- d: J" A
8.5 Effect Size Models with Moderators Using a Mix of IPD and AD......Page 133
* i5 I7 k: M6 C4 K' T! P1 S8.5.1 Two-Stage Methods for Meta-regression with a Mix of IPD and AD......Page 1346 |4 `7 m9 c2 f8 r' Z2 z/ I
8.5.2 One-Stage Method for Meta-regression with a Mix of IPD and AD......Page 135$ {$ [' B+ l; `: g9 G9 K3 j
8.5.4 One-Stage Meta-regression with a Mix of IPD and AD......Page 136
8 |9 O! o! P  d7 C( h8.5.4.1 Example: One-Stage Method for Meta-regression with Correlationsƒ......Page 137, Q, q* X# {( o6 R5 j2 O9 l
SAS Code for Simple Random Effects Model Using the Two-Step Method......Page 138
/ s$ I. v6 T4 t8 F. F8 H, ^( G3 gOutput from Two-Stage Simple Random Effects Model......Page 139: J) q& R  a6 z5 ^8 c4 Y3 n$ c
SAS Code for Meta-regression Using the Two-Stage Method......Page 140
" \4 g- w9 @/ {: W; o1 nSAS Code for Simple Random Effects Model Using the One-Stage Model......Page 141
( X! {7 A6 f5 I+ B, UOutput from One-Stage Simple Random Effects Model......Page 143
2 h, @2 w: x$ c7 z  S% {Output for Meta-regression Using the One-Step Method......Page 144; Y2 ^, X, `* x" `% C4 f+ ]
References......Page 145
0 u  p/ p* I4 o) k9.1 Background......Page 148
5 B1 ~1 `7 z" `1 g! `- _1 @! R9.1.1 The Preventive Health Services (2009) Report on Breast Cancer Screening......Page 149
" m' `" |# R  \& x4 ]' T& v5 R9.2.1 Surface Similarity......Page 150) O) S& ~: U4 h4 |
9.2.2 Ruling Out Irrelevancies......Page 151
. \- L6 K- h: }, c% a, B9.2.3 Making Discriminations......Page 152! @+ J9 q$ c6 V
9.2.5 Causal Explanation......Page 153( r- r5 z2 [' K& v7 G
9.3 Suggestions for Generalizing from a Meta-analysis......Page 1544 @, U  f: R! ^  u
References......Page 1554 T6 ]5 |) }' Y
10.2 Understanding the Research Problem......Page 158
- [; {  ?- |* D' Z! Z8 l10.3 Having an a Priori Plan for the Meta-analysis......Page 159- C* k: g- l- _. G3 j! @0 T8 x
10.4 Carefully and Thoroughly Interpret the Results of Meta-analysis......Page 160
/ c# s4 t7 `0 Y. z! x2 kReferences......Page 161
/ h0 q: q3 r; J' d11.1 Sirin (2005) Meta-analysis on the Association Between Measures of Socioeconomic Status and Academic Achievement......Page 1626 R2 r; |. t- x' o6 B
11.2 Hackshaw et al. (1997) Meta-analysis on Exposure to Passive Smoking and Lung Cancer......Page 164
7 A7 o( R+ }2 E2 l6 R11.3 Eagly et al. (2003) Meta-analysis on Gender Differences in Transformational Leadership......Page 1660 \( G3 l! K) Z9 Q# d
References......Page 167! [0 A4 b1 s, M( Y9 h- A7 [, Q3 Q
Index......Page 168
$ [- ?5 S1 u) G4 p9 P$ t* c2 V) ?+ H* k1 J1 v
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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
/ T* k/ J5 b% Y% W楼主牛逼,有没有关于网络meta的书啊
  o1 Z  g5 G# l0 q
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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