公卫人

 找回密码
 立即注册

QQ登录

只需一步,快速开始

不劳无获:如何获取钢镚? 因为论坛,所以相逢。 捐赠百科答题至尊

公卫考研:一起风雨兼程 因为梦想,所以努力。 真题答案政治英语

职称考试:诸君逢考必过 因为热爱,所以执着。 模拟考场技能执医中级

查看: 8662|回复: 21

[分享] [福利] 8本Meta分析英文原版电子书(免费PDF下载)

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

注册后推荐绑定QQ,之后方才可以使用下方的“用QQ帐号登录”。

您需要 登录 才可以下载或查看,没有帐号?立即注册

x
本帖最后由 sampson2010 于 2015-3-3 21:18 编辑 $ R& G3 N! U! j0 ^! C
% N7 p" m5 H- H8 o. G4 q& B
Advances in Meta-Analysis. |% }; A  L$ R2 J5 M9 `+ L  a
dfb1ae72d031988dd5514bba6255e827-d.jpg
. m/ U( h( i  q/ xAuthor(s):Terri D. Pigott) a5 D0 x/ y$ O% u# j
Series: Statistics for Social and Behavioral Sciences# ?' {$ J# x$ O: x
Publisher: Springer
8 o2 R: T. r) ~. MYear: 2012        $ j4 C$ {$ G2 q* z# ^
Edition: 2012) Z0 t3 H! r5 ?+ E
Language: English        & m2 ?. j0 I) ]# f+ m
Pages: 170

% w: G+ p; r& p% O6 M$ A0 `& m2 T
2 b$ L* H' f, fTable of contents : ) C5 l; {5 h+ t$ e: U, x; V) Y
Cover......Page 1
; I( K$ k) f7 w' H) _- RStatistics for Social and Behavioral Sciences......Page 20 h' |5 _6 _1 j3 o9 K2 D
Advances in Meta-Analysis......Page 4) h/ M* s7 p/ @6 H6 @
ISBN 9781461422778......Page 5
5 {, i5 a( L$ D: Z8 ^* B: mAcknowledgements......Page 8. V5 D9 L- J" U/ k0 {
Contents......Page 10
( ?* T2 K: ?/ N+ ^/ E0 q# {1.1 Background......Page 16
' L0 e( ]. o( w+ v1.2 Planning a Systematic Review......Page 17
$ Q$ O  A5 ~. m- P1.4 Interpreting Results from a Meta-analysis......Page 19
- Z) v( ^4 a5 b7 ]1.5 What Do Readers Need to Know to Use This Book?......Page 20
* Z+ A; l: c5 k! JReferences......Page 21" q! }/ l$ s' T$ L' R, ?4 \8 q
2.2 Introduction to Notation and Basic Meta-analysis......Page 22
- F9 V2 q0 H: P( T% Q- M2.3 The Random Effects Mean and Variance......Page 23- B2 G+ b3 T, H/ G6 F" P* F2 y
2.4.2 Correlation Coefficient......Page 25
& `& u+ f1 L" ~3 S3 B& w2.4.3 Log Odds Ratio......Page 267 t. t# i7 s' R+ X2 z, {, B' Q
References......Page 27
' V. e" p; O. j0 x1 U( r: C( C3.1 Background......Page 28  o& t. [- r4 |; a/ N' k4 J
3.2 Deciding on Important Moderators of Effect Size......Page 29! ^+ I& K) G9 o* u
3.3 Choosing Among Fixed, Random and Mixed Effects Modelsƒ......Page 317 @5 r0 g* f6 v9 x8 d! _. C. Q
3.4 Computing the Variance Component in Random and Mixed Models......Page 33
) Z2 P' E- f" L0 v( s: _2 v( e4 _3.4.1 Example......Page 35" b  p% d3 O' t8 ~' {" B
3.5 Confounding of Moderators in Effect Size Models......Page 36: S& Y( k9 P: f; P, N0 s# m
3.5.1 Example......Page 38
% K+ [0 f/ S2 ^, ]  g9 V3.6.1 Example......Page 40
- {6 p% O! X3 ^+ Y! {9 b- O$ `( Y3.7 Interpretation of Moderator Analyses......Page 43
, o/ ~, q# Q' f; @4 C2 fComputing the Variance Component Using SAS......Page 44" _1 l' a1 u5 b/ B6 C
Computing the Variance Component Using R......Page 453 T* k9 g+ \* [3 q8 T: g! ^
Computing the Fixed Effects Meta-regression Using SAS......Page 460 B3 {7 u+ T8 O2 u
References......Page 47
. @1 v9 B* M4 e  q4.1 Background......Page 50
% u: Z1 u/ |, s4.2 Fundamentals of Power Analysis......Page 52
$ c0 L7 J' V% i" E) [8 [4.3.1 Z-Test for the Mean Effect Size in the Fixed Effects Modelƒ......Page 54
  q, I6 {! @  c% t' I4.3.2 The Power of the Test of the Mean Effect Size in Fixed Effects Models......Page 56! b, O! E! t  p/ w" l
4.3.3 Deciding on Values for Parameters to Compute Power......Page 57, M7 @+ _! o3 y/ a- v3 O4 Z
4.3.4 Example: Computing the Power of the Test of the Mean......Page 580 L9 i% h, f  v# p# y
4.3.5 Example: Computing the Number of Studies Needed to Detect an Important Fixed Effects Mean......Page 60
' j# q2 `4 E- e8 r$ d' u4.3.6 Example: Computing the Detectable Fixed Effects Mean in a Meta-analysis......Page 616 M3 j5 p8 ?1 R# b
4.4 Test of the Mean Effect Size in the Random Effects Model......Page 62
; ?& n3 O2 A. C6 k3 E: t4.4.1 The Power of the Test of the Mean Effect Size in Random Effects Models......Page 63
/ [$ B0 i- A  _4.4.2 Positing a Value for tau2 for Power Computations in the Random Effects Model......Page 64
6 S) v+ [5 z& ~1 U  Q( j4.4.3 Example: Estimating the Power of the Random Effects Mean......Page 650 X9 ~: e  U4 ^4 h7 e
4.4.4 Example: Computing the Number of Studies Needed to Detect an Important Random Effect Mean......Page 66& q6 ]( }& |+ y/ b
Excel......Page 67
) |& D# G! u% O# IReferences......Page 68
% T7 c$ \5 I+ ?% C  _: m0 N7 {7 K5 r5.1 Background......Page 70
, R' G4 a0 w5 X  i  J5.2.1 The Power of the Test of Homogeneity in a Fixed Effects Model......Page 717 e  Y6 D1 m' c, e% V* P; {$ |
5.2.2 Choosing Values for the Parameters Needed to Compute Power of the Homogeneity Test in Fixed Effects Models......Page 720 |' ?  i- w* c+ O& j) y
5.2.3 Example: Estimating the Power of the Test of Homogeneity in Fixed Effects Models......Page 73
2 x  ^; K5 Q1 p5.3 The Test of the Significance of the Variance Component in Random Effects Models......Page 74
2 V% ]# Q0 y! w0 B# A: f2 A7 N5.3.1 Power of the Test of the Significance of the Variance Component in Random Effects Models......Page 75: [; D. L: C; p6 A
5.3.2 Choosing Values for the Parameters Needed to Compute the Variance Component in Random Effects Models......Page 76- h) x. [8 M" t7 p) N1 ^- f8 B
5.3.3 Example: Computing Power for Values of tau2, the Variance Component......Page 77
! j$ B6 a* w9 f: d7 D- X" ISAS......Page 79$ e0 Y3 z5 e/ i4 }
R......Page 80, p' N  Z* A& f& P% ^& z/ Y- ?! A
References......Page 81* i) q. e% d9 P- z
6.1 Background......Page 82
) _4 N' R7 Y2 z6 u  r6.2.2 Power of the Test of Between-Group Homogeneity, QB, in Fixed Effects Models......Page 83
7 ^2 E* e1 E- e) |% S# G4 x& ?$ W7 I1 N6.2.4 Example: Power of the Test of Between-Group Homogeneity in Fixed Effects Models......Page 85
% d  z# H# Q% B% |, F+ F6.2.5 Power of the Test of Within-Group Homogeneity, QW, in Fixed Effects Models......Page 86  ^( i. y8 Z% F
6.2.6 Choosing Parameters for the Test of QW in Fixed Effects Models......Page 87# i; U8 S7 s3 z
6.2.7 Example: Power of the Test of Within-Group Homogeneity in Fixed Effects Models......Page 88
0 B0 J4 {0 B4 ]6.3.1 Power of Test of Between-Group Homogeneity in the Random Effects Model......Page 89' j+ L2 ~9 z+ s2 Q4 H
6.3.3 Example: Power of the Test of Between-Group Homogeneity in Random Effects Models......Page 91
; M' Q3 T$ t# P8 M$ j4 m( X+ OReferences......Page 93: J. ~) [9 W% H. i
7.1 Background......Page 94
2 @4 N1 r- f9 N5 T6 |7.2.1 Identification of Publication Bias......Page 959 Q2 ~9 @9 {1 R
7.2.1.1 Example of Funnel Plot......Page 96+ ]/ }2 q+ c  J* `4 B) j$ _& ^0 Q
7.2.2 Assessing the Sensitivity of Results to Publication Bias......Page 97
0 i+ [: A% d; A2 z7.3 Missing Effect Sizes in a Meta-analysis......Page 100
/ |* g' o. f; {/ C$ p7.4 Missing Moderators in Effect Size Models......Page 101% q7 U6 j  c; O6 k' i& _
7.5 Theoretical Basis for Missing Data Methods......Page 102- [' B. l' q& Z9 H4 ~& i& u9 c; p
7.5.1 Multivariate Normality in Meta-analysis......Page 103( p" l5 Q) X, P8 m
7.5.2 Missing Data Mechanisms or Reasons for Missing Data......Page 104- N) P) I0 b0 W
7.6.1 Complete-Case Analysis......Page 105
8 |0 D% b& K8 N; e& J4 c7.6.1.1 Example: Complete-Case Analysis......Page 1069 Y% L$ n0 E/ b. x
7.6.2 Available Case Analysis or Pairwise Deletion......Page 107
4 v5 M3 l, _9 _! h1 d! ^7.6.3 Single Value Imputation with the Complete Case Mean......Page 108
* v9 c3 X! Q1 ?" l! Q  j! w7.6.3.1 Example: Mean Imputation......Page 109
9 Z6 Z: o' K" Z5 K  S* D$ X7.6.4 Single Value Imputation Using Regression Techniques......Page 110
8 h9 D( N3 S* e; N: k4 M7.6.4.1 Example: Regression Imputation......Page 111" E/ I4 l( q6 s# Z
7.7.1 Maximum-Likelihood Methods for Missing Data Using the EM Algorithm......Page 112
  ]* I0 C. j% W  [& D7.7.1.1 Example Using the EM Algorithm......Page 113
3 }8 U1 K. S5 `9 E8 g/ M4 f7.7.2.1 Generating Multiple Imputations......Page 114
9 {- b& k) P* [9 G. T7.7.2.3 Combining the Estimates......Page 115
  h, ^7 k% S6 y$ O9 M% U3 HR Programs......Page 1170 C& i) Y1 R7 ~$ U9 X
SAS Proc MI......Page 119
4 y6 a3 e8 p! Z# O9 o0 p: V; V& ]! hReferences......Page 1219 c( f! C6 k3 l% ~
8.1 Background......Page 1241 K' T) H2 U: ]) i; u0 d
8.2 The Potential for IPD Meta-analysis......Page 125
  O' V% n, n2 Y8.3.1 Simple Random Effects Models with Aggregated Data......Page 127+ C+ D0 c7 W  g" x
8.3.2.1 Example: Two-Stage Method Using Correlation as the Effect Size......Page 1296 D6 X' `' ?& b3 ^' r
8.4.1 IPD Model for the Standardized Mean Difference......Page 130
* e% ]* R2 j+ @8.4.3 Model for the One-Stage Method with Both IPD and AD......Page 1314 j# @: U9 H8 D. W
8.5 Effect Size Models with Moderators Using a Mix of IPD and AD......Page 133
$ K8 f7 O1 a, }4 K9 K5 K' w. ]" n8.5.1 Two-Stage Methods for Meta-regression with a Mix of IPD and AD......Page 134
  b4 [: A  @$ Y9 I' Z8.5.2 One-Stage Method for Meta-regression with a Mix of IPD and AD......Page 135! p7 y, \- l1 {, ^7 V( F; i
8.5.4 One-Stage Meta-regression with a Mix of IPD and AD......Page 136/ R) [! H# M$ `' u. v; c8 p& y
8.5.4.1 Example: One-Stage Method for Meta-regression with Correlationsƒ......Page 137
! V. E2 d. O1 e' x& ASAS Code for Simple Random Effects Model Using the Two-Step Method......Page 138
, a- `$ p# q! m) }/ B% J' x! _2 dOutput from Two-Stage Simple Random Effects Model......Page 139- z/ L9 c# V" F% h/ [! P& H
SAS Code for Meta-regression Using the Two-Stage Method......Page 140
0 S* j; M. M( I" j/ f) G! I7 o" y/ ?SAS Code for Simple Random Effects Model Using the One-Stage Model......Page 141# n0 J( O- e0 _. Z) q; n5 z
Output from One-Stage Simple Random Effects Model......Page 1434 T, `& c/ r) a9 V3 j* i7 r2 i8 D
Output for Meta-regression Using the One-Step Method......Page 144
% v) ]) M$ G' C8 B' |% zReferences......Page 145
" L8 @. m$ s% Z9.1 Background......Page 148
6 Z& q5 I& e" z# A5 l. B- T& U9.1.1 The Preventive Health Services (2009) Report on Breast Cancer Screening......Page 149( G% c3 b% q9 `
9.2.1 Surface Similarity......Page 150; C, _4 I! X% U% c
9.2.2 Ruling Out Irrelevancies......Page 151& T, J+ ]/ y; y* ^- |
9.2.3 Making Discriminations......Page 152
2 G) p2 ^( g$ z5 ]4 |9.2.5 Causal Explanation......Page 153
0 o2 ]8 O+ W8 j$ D+ C9.3 Suggestions for Generalizing from a Meta-analysis......Page 1542 w4 b* j) Y1 K0 G) O
References......Page 155
; W* n4 F; c; ~, b8 A; q8 s7 A10.2 Understanding the Research Problem......Page 158
1 k, _& n! P* ]7 k  {" ^& J& H3 {10.3 Having an a Priori Plan for the Meta-analysis......Page 159
1 }1 q5 x* x# M- j' q10.4 Carefully and Thoroughly Interpret the Results of Meta-analysis......Page 160) b/ ]# a5 }; \
References......Page 1612 c5 e2 [- A% u9 w/ j$ s" G) P  |
11.1 Sirin (2005) Meta-analysis on the Association Between Measures of Socioeconomic Status and Academic Achievement......Page 162
, l2 l  c1 m# g, m( X. b" I11.2 Hackshaw et al. (1997) Meta-analysis on Exposure to Passive Smoking and Lung Cancer......Page 1641 _3 ?- Z  `' u$ j
11.3 Eagly et al. (2003) Meta-analysis on Gender Differences in Transformational Leadership......Page 166
& A3 N& [0 i* Q3 UReferences......Page 167
5 @4 @7 l6 E- U3 ^) B/ O% @Index......Page 168& q, ?* |( B2 u5 U
7 Z, m4 h# [  z  z5 q
Advances in Meta-Analysis (2012).pdf (1.03 MB, 下载次数: 609)

本帖被以下淘专辑推荐:

猫猫咪吖 发表于 2015-3-15 21:23:02 | 显示全部楼层
看不懂!
回复

使用道具 举报

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~!
回复

使用道具 举报

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。
回复

使用道具 举报

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
回复

使用道具 举报

insect16 发表于 2015-6-26 11:25:52 | 显示全部楼层
感谢楼主无私分享
回复

使用道具 举报

MLJ要奋斗 发表于 2015-7-2 10:16:30 | 显示全部楼层
回复

使用道具 举报

 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
3 \7 j* V4 t4 B" b9 y/ E! g楼主牛逼,有没有关于网络meta的书啊

% _6 G* i& ~  a$ ~最近忙于毕业,没时间整理,等闲下来了再发帖,记得关注哦!
回复

使用道具 举报

fisher163 发表于 2015-8-14 20:13:31 | 显示全部楼层
可以点个赞
回复

使用道具 举报

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。
回复

使用道具 举报

您需要登录后才可以回帖 登录 | 立即注册

本版积分规则

提现|充值|至尊会员|接种|公卫人 ( 沪ICP备06060850号-3 )

GMT+8, 2019-8-21 11:44 , Processed in 0.164462 second(s), 35 queries , Gzip On.

Powered by Discuz! X3.4

© 2001-2017 Comsenz Inc.

快速回复 返回顶部 返回列表