Description Usage Arguments Details Value Author(s) References See Also Examples

Wrapper function to perform meta-analysis for a single outcome of a Cochrane Intervention review.

1 2 3 4 5 6 7 8 9 10 11 12 | ```
metacr(x, comp.no=1, outcome.no=1,
method, sm,
level=gs("level"), level.comb=gs("level.comb"),
comb.fixed, comb.random,
hakn=FALSE,
method.tau="DL",
tau.common=FALSE,
prediction=gs("prediction"), level.predict=gs("level.predict"),
swap.events, logscale,
backtransf=gs("backtransf"),
title, complab, outclab,
keepdata=gs("keepdata"), warn=FALSE)
``` |

`x` |
An object of class |

`comp.no` |
Comparison number. |

`outcome.no` |
Outcome number. |

`method` |
A character string indicating which method is to be used
for pooling of studies. One of |

`sm` |
A character string indicating which summary measure
( |

`level` |
The level used to calculate confidence intervals for individual studies. |

`level.comb` |
The level used to calculate confidence intervals for pooled estimates. |

`comb.fixed` |
A logical indicating whether a fixed effect meta-analysis should be conducted. |

`comb.random` |
A logical indicating whether a random effects meta-analysis should be conducted. |

`hakn` |
A logical indicating whether the method by Hartung and Knapp should be used to adjust test statistics and confidence intervals. |

`method.tau` |
A character string indicating which method is used
to estimate the between-study variance |

`tau.common` |
A logical indicating whether tau-squared should be the same across subgroups. |

`prediction` |
A logical indicating whether a prediction interval should be printed. |

`level.predict` |
The level used to calculate prediction interval for a new study. |

`swap.events` |
A logical indicating whether events and non-events should be interchanged. |

`logscale` |
A logical indicating whether effect estimates are entered on log-scale. |

`backtransf` |
A logical indicating whether results should be
back transformed in printouts and plots. If |

`title` |
Title of meta-analysis / systematic review. |

`complab` |
Comparison label. |

`outclab` |
Outcome label. |

`keepdata` |
A logical indicating whether original data (set) should be kept in meta object. |

`warn` |
A logical indicating whether warnings should be printed
(e.g., if |

Cochrane Intervention reviews are based on the comparison of two interventions. Each Cochrane Intervention review can have a variable number of comparisons. For each comparison, a variable number of outcomes can be define. For each outcome, a seperate meta-analysis is conducted. Review Manager 5 (RevMan 5) is the current software used for preparing and maintaining Cochrane Reviews (http://community.cochrane.org/tools/review-production-tools/revman-5).

This wrapper function can be used to perform meta-analysis for a
single outcome of a Cochrane Intervention review. Internally, R
functions `metabin`

, `metacont`

, and `metagen`

are
called - depending on the definition of the outcome in RevMan 5.

Note, it is recommended to specify the RevMan 5 before executing `metacr`

, i.e.,

[] settings.meta("revman5")

An object of class `"meta"`

and `"metabin"`

,
`"metacont"`

, or `"metagen"`

depending on outcome type
utilised in Cochrane Intervention review for selected outcome.

Guido Schwarzer [email protected]

*Review Manager (RevMan)* [Computer program]. Version
5.3. Copenhagen: The Nordic Cochrane Centre, The Cochrane
Collaboration, 2014.

`metabin`

, `metacont`

, `metagen`

, `read.rm5`

, `settings.meta`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | ```
# Locate export data file "Fleiss93_CR.csv"
# in sub-directory of package "meta"
#
filename <- system.file("data/Fleiss93_CR.csv.gz", package = "meta")
#
Fleiss93_CR <- read.rm5(filename)
# Choose RevMan 5 settings and store old settings
#
oldset <- settings.meta("revman5")
# Same result as R command example(Fleiss93):
#
metacr(Fleiss93_CR)
# Same result as R command example(Fleiss93cont):
#
metacr(Fleiss93_CR, 1, 2)
forest(metacr(Fleiss93_CR, 1, 2))
# Change summary measure to RR
#
m1 <- metacr(Fleiss93_CR)
update(m1, sm="RR")
# Use old settings
#
settings.meta(oldset)
``` |

```
Loading 'meta' package (version 4.8-4).
Type 'help(meta)' for a brief overview.
** Use RevMan 5 settings (R package meta) **
-------- --------- --------------
Argument New value Previous value
-------- --------- --------------
RR.cochrane TRUE FALSE
layout "RevMan5" "meta"
test.overall TRUE FALSE
test.subgroup TRUE FALSE
test.effect.subgroup TRUE FALSE
digits.I2 0 1
digits.tau2 2 4
CIseparator ", " "; "
Review: Fleiss93_CR.csv.gz
Comparison: 1 Examples from Fleiss (1993)
Outcome: 1.1 Aspirin for Preventing Death after Myocardial Infarction
OR 95%-CI %W(fixed)
MRC-1 0.7197 [0.4890, 1.0593] 3.2
CDP 0.6808 [0.4574, 1.0132] 3.1
MRC-2 0.8029 [0.6065, 1.0629] 5.7
GASP 0.8007 [0.4863, 1.3186] 1.8
PARIS 0.7981 [0.5526, 1.1529] 3.2
AMIS 1.1327 [0.9347, 1.3728] 10.2
ISIS-2 0.8950 [0.8294, 0.9657] 72.9
Number of studies combined: k = 7
OR 95%-CI z p-value
Fixed effect model 0.8969 [0.8405, 0.9570] -3.29 0.0010
Quantifying heterogeneity:
tau^2 = 0.01; H = 1.29 [1.00, 1.99]; I^2 = 40% [0%, 75%]
Test of heterogeneity:
Q d.f. p-value
9.95 6 0.1269
Details on meta-analytical method:
- Mantel-Haenszel method
Review: Fleiss93_CR.csv.gz
Comparison: 1 Examples from Fleiss (1993)
Outcome: 1.2 Mental Health Treatment versus Control
MD 95%-CI %W(fixed)
Davis -1.5000 [-4.7855, 1.7855] 2.8
Florell -1.2000 [-2.0837, -0.3163] 38.6
Gruen -2.4000 [-6.1078, 1.3078] 2.2
Hart 0.2000 [-0.7718, 1.1718] 31.9
Wilson -0.8800 [-1.9900, 0.2300] 24.5
Number of studies combined: k = 5
MD 95%-CI z p-value
Fixed effect model -0.7094 [-1.2585, -0.1603] -2.53 0.0113
Quantifying heterogeneity:
tau^2 = 0.19; H = 1.19 [1.00, 1.91]; I^2 = 29% [0%, 73%]
Test of heterogeneity:
Q d.f. p-value
5.66 4 0.2260
Details on meta-analytical method:
- Inverse variance method
Review: Fleiss93_CR.csv.gz
Comparison: 1 Examples from Fleiss (1993)
Outcome: 1.1 Aspirin for Preventing Death after Myocardial Infarction
RR 95%-CI %W(fixed)
MRC-1 0.7420 [0.5223, 1.0543] 2.9
CDP 0.6993 [0.4828, 1.0129] 2.8
MRC-2 0.8270 [0.6487, 1.0545] 5.4
GASP 0.8209 [0.5269, 1.2789] 1.7
PARIS 0.8193 [0.5927, 1.1326] 3.0
AMIS 1.1183 [0.9411, 1.3289] 9.5
ISIS-2 0.9142 [0.8596, 0.9722] 74.7
Number of studies combined: k = 7
RR 95%-CI z p-value
Fixed effect model 0.9136 [0.8657, 0.9642] -3.29 0.0010
Quantifying heterogeneity:
tau^2 = 0.01; H = 1.29 [1.00, 1.98]; I^2 = 40% [0%, 75%]
Test of heterogeneity:
Q d.f. p-value
9.93 6 0.1277
Details on meta-analytical method:
- Mantel-Haenszel method
```

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