[R] help with metasens

[Michael Dewey]

Dear Mario

I do not use metasens myself so cannot be of direct help but I have 
looked at your dataset and it does seem rather strange (as you perhaps 
know). You have two quite large studies with very large hazard ratios 
and if we ignore them all the rest of the studies fall on a diagonal 
bacn indicative of extreme small study bias.

One thing you could consider is to use metafor and within it use the hc 
function which uses a different approach due to Henmi and Copas (the 
same Copas).

On 12/08/2015 15:19, petretta at unina.it wrote:
> Dear all,
>
> I use R 3.1.1 for Windows (x 64).
>
> I performed a meta-analysis of hazard ratio using the below reported
> Dataset and metagen function from package meta.
>
> meta1<-metagen(Dataset$lnHR, Dataset$seHR, sm="HR")
>
> Thereafter, I try to use the copas function from package metasens.
>
> cop1<-copas(meta1)
>
>
> and I have these 3 warnings:
>
> Warning in sqrt(solve(junk2$hessian + 1e-08)[1, 1]) :
> NaN was produced
> Warning in sqrt(solve(junk2$hessian + 1e-08)[1, 1]) :
> NaN was produced
> Warning in sqrt(solve(junk2$hessian + 1e-08)[1, 1]) :
> NaN was produced
>
> If I try:
> plot (cop1)
>
>   I have:
> ERROR:
> object "is.relative.effect" not found
>
> Any suggestion is welcome.
>
> The Dataset is:
>
>     id Year      lnHR       seHR
> 1   1 2001 0.6881346 0.06940859
> 2   2 2001 1.4036430 0.60414338
> 3   3 2002 0.7419373 0.28897730
> 4   4 2003 1.5475625 0.45206678
> 5   5 2003 1.4816046 0.44859666
> 6   6 2005 0.9162908 0.17166950
> 7   7 2006 1.2697605 0.34205049
> 8   8 2009 0.8960880 0.24626434
> 9   9 2011 1.5040774 0.24683516
> 10 10 2012 0.4510756 0.17213355
> 11 11 2008 0.9895412 0.26590857
> 12 12 2009 2.8094027 0.61304092
> 13 13 2010 0.9162908 0.21362771
> 14 14 2011 0.5068176 0.15060408
> 15 15 2012 3.0027080 0.27239493
> 16 16 2013 1.9837563 0.55793673
> 17 17 2013 3.0492730 0.18798657
> 18 18 2014 1.2974632 0.44759619
> 19 19 2014 0.8241754 0.39551640
> 20 20 2014 2.2617631 0.56545281
>
> The code used are:
>
> meta1<-metagen(Dataset$lnHR, Dataset$seHR, sm="HR")
>
>> meta1
>        HR             95%-CI %W(fixed) %W(random)
> 1   1.99 [ 1.7369;  2.2800]     42.92       5.99
> 2   4.07 [ 1.2455; 13.2997]      0.57       3.71
> 3   2.10 [ 1.1919;  3.7000]      2.48       5.28
> 4   4.70 [ 1.9378; 11.3998]      1.01       4.47
> 5   4.40 [ 1.8264; 10.5998]      1.03       4.49
> 6   2.50 [ 1.7857;  3.5000]      7.02       5.75
> 7   3.56 [ 1.8209;  6.9599]      1.77       5.03
> 8   2.45 [ 1.5120;  3.9700]      3.41       5.47
> 9   4.50 [ 2.7740;  7.2999]      3.39       5.47
> 10  1.57 [ 1.1204;  2.2000]      6.98       5.75
> 11  2.69 [ 1.5974;  4.5300]      2.92       5.38
> 12 16.60 [ 4.9921; 55.1988]      0.55       3.67
> 13  2.50 [ 1.6447;  3.8000]      4.53       5.60
> 14  1.66 [ 1.2357;  2.2300]      9.12       5.81
> 15 20.14 [11.8085; 34.3497]      2.79       5.36
> 16  7.27 [ 2.4357; 21.6996]      0.66       3.94
> 17 21.10 [14.5971; 30.4998]      5.85       5.69
> 18  3.66 [ 1.5223;  8.7999]      1.03       4.49
> 19  2.28 [ 1.0502;  4.9499]      1.32       4.76
> 20  9.60 [ 3.1693; 29.0794]      0.65       3.90
>
> Number of studies combined: k=20
>
>                           HR           95%-CI       z  p.value
> Fixed effect model   2.7148 [2.4833; 2.9679] 21.9628 < 0.0001
> Random effects model 3.9637 [2.7444; 5.7247]  7.3426 < 0.0001
>
> Quantifying heterogeneity:
> tau^2 = 0.5826; H = 3.56 [3.04; 4.16]; I^2 = 92.1% [89.2%; 94.2%]
>
> Test of heterogeneity:
>        Q d.f.  p.value
>   240.64   19 < 0.0001
>
> Details on meta-analytical method:
> - Inverse variance method
> - DerSimonian-Laird estimator for tau^2
>
>> cop1<-copas(meta1)
>
> Warning in sqrt(solve(junk2$hessian + 1e-08)[1, 1]) :
> NaN was produced
>
>> plot (cop1)
>
> ERROR:
> object "is.relative.effect" not found
>
> -------------------------------------------------------
> Mario Petretta
> Associate Professor of Internal Medicine
> Department of Translational Medical Sciences
> Naples University Federico II Italy
>
>
>
> ----
> 5x1000 AI GIOVANI RICERCATORI
> DELL'UNIVERSITÀ DI NAPOLI
> Codice Fiscale: 00876220633
> www.unina.it/Vademecum5permille
>
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-- 
Michael
http://www.dewey.myzen.co.uk/home.html