
R version 4.2.2 (2022-10-31 ucrt) -- "Innocent and Trusting"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)

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[原来保存的工作空间已还原]

> library(xlsx)
> library(meta)
载入需要的程辑包：metadat
Loading 'meta' package (version 7.0-0).
Type 'help(meta)' for a brief overview.
Readers of 'Meta-Analysis with R (Use R!)' should install
older version of 'meta' package: https://tinyurl.com/dt4y5drs
Warning messages:
1: 程辑包‘meta’是用R版本4.2.3 来建造的 
2: 程辑包‘metadat’是用R版本4.2.3 来建造的 
> metagen <- read.xlsx("review.xlsx",3)
> metagen <- cbind(metagen,lnhr,se)
Error in data.frame(..., check.names = FALSE) : 找不到对象'lnhr'
> se <-(metagen $ uci - metagen $ lci)/ (2*1.96)
> lnhr<- log(metagen$ hr)
> metagen <- cbind(metagen,lnhr,se)
> m <- metagen(TE=metagen $ lnhr,seTE=metagen $ se,studlab=paste(metagen $ study,metagen $year,sep="/"),sm="HR",backtransf=TRUE)
> m <- metagen(TE=metagen $ lnhr,seTE=metagen $ se,studlab=paste(metagen $ study,metagen $year,sep="/"),sm="HR",backtransf=TRUE)
> tfl <- trimfill(m)
> summary(tfl,comb.fixed=FALSE)
                       HR                 95%-CI %W(random)
Bjørneklett/2011   1.5000 [0.7449;       3.0206]        6.4
Baek/2012          2.2900 [1.0710;       4.8966]        5.7
Lin/2015           3.0550 [0.0853;     109.4769]        0.3
Mashitani/2017     2.1900 [0.5706;       8.4054]        2.2
Orlandi/2018       2.5000 [0.9669;       6.4642]        4.1
Lin/2018           2.7130 [1.5961;       4.6115]        9.1
Bobart/2019        1.4580 [0.0043;     489.0471]        0.1
Wu/2020            2.0450 [0.9249;       4.5217]        5.4
Okada/2020         4.1100 [0.7323;      23.0667]        1.4
Precil/2020        1.0240 [0.4197;       2.4985]        4.5
Yoshida/2020       1.4900 [1.2078;       1.8382]       17.3
Ebbestad/2022      4.1970 [0.0000; 7214519.5816]        0.0
Lv/2017            3.3100 [0.0463;     236.7180]        0.2
Vandenbussche/2019 1.0980 [0.6894;       1.7489]       10.5
Fogh/2021          2.3600 [2.0211;       2.7557]       18.8
He/2021            1.3700 [0.9849;       1.9056]       13.9

Number of studies: k = 16 (with 0 added studies)

                         HR           95%-CI    z  p-value
Random effects model 1.7681 [1.4286; 2.1883] 5.24 < 0.0001

Quantifying heterogeneity:
 tau^2 = 0.0568 [0.0000; 0.1211]; tau = 0.2383 [0.0000; 0.3479]
 I^2 = 45.1% [1.3%; 69.4%]; H = 1.35 [1.01; 1.81]

Test of heterogeneity:
     Q d.f. p-value
 27.30   15  0.0264

Details on meta-analytical method:
- Inverse variance method
- Restricted maximum-likelihood estimator for tau^2
- Q-Profile method for confidence interval of tau^2 and tau
- Trim-and-fill method to adjust for funnel plot asymmetry (L-estimator)
Warning message:
Additional arguments provided in '...' are ignored. 
> 
