Description Usage Arguments Value References See Also Examples

Summary a model of class `multipletables`

fitted by `multipletables`

.

1 2 |

`object` |
an object inheriting from class |

`...` |
additional arguments; currently none is used. |

A list with the following components:

`model` |
the value of |

`measure` |
the value of |

`cov.matrix` |
the estimated covariance matrix of the estimated parameters in the transformed scales |

`hessian` |
the estimated hessian matrix of the estimated parameters in the transformed scales |

`overall` |
a list of two components that contain the overall measure (e.g., overall OR) and its 95% equal-tail credible interval. |

`studynames` |
a character string indicating all the study names |

`chi2` |
the chi-square test statistics of the likelihood ratio test |

`pvalue` |
the p-value of the likelihood ratio test |

`alpha` |
the value of |

`MLE` |
a numeric vector of the estimated hyperparameters in the
following order: |

`studyspecific` |
a Numeric matrix with columns being the posterior means, the lower bound, and the upper bound of the credible/confidence intervals of study-specific and overall measure. |

Luo, S., Chen, Y., Su, X., Chu, H., (2014). mmeta: An R Package for Multivariate Meta-Analysis. Journal of Statistical Software, 56(11), 1-26.

Chen, Y., Luo, S., (2011a). A Few Remarks on "Statistical Distribution of the Difference of Two Proportions' by Nadarajah and Kotz, Statistics in Medicine 2007; 26(18):3518-3523" . Statistics in Medicine, 30(15), 1913-1915.

Chen, Y., Chu, H., Luo, S., Nie, L., and Chen, S. (2014a). Bayesian analysis on meta-analysis of case-control studies accounting for within-study correlation. Statistical Methods in Medical Research, doi: 10.1177/0962280211430889. In press.

Chen, Y., Luo, S., Chu, H., Su, X., and Nie, L. (2014b). An empirical Bayes method for multivariate meta-analysis with an application in clinical trials. Communication in Statistics: Theory and Methods. In press.

Chen, Y., Luo, S., Chu, H., Wei, P. (2013). Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials. Statistics in Biopharmaceutical Research, 5(2), 142-155.

`multipletables`

`plot.multipletables`

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 30 31 32 33 | ```
#library(mmeta)
# Analyze the dataset colorectal to conduct exact inference of the odds ratios
#data(colorectal)
#multiple.OR <- multipletables(data=colorectal, measure="OR", model="Sarmanov", method="exact")
# Generate the forest plot with 95% CIs of study-specific odds ratios
#and 95% CI of overall odds ratio
#plot(multiple.OR, type="forest", addline=1)
# Plot the posterior density functions of some target studies in an overlaying manner
#plot(multiple.OR, type="overlap", select=c(4,14,16,20))
# Plot the posterior density functions of some target studies in a
#side-by-side manner
#plot(multiple.OR, type="sidebyside", select=c(4,14,16,20), ylim=c(0,2.7), xlim=c(0.5,1.5))
# Analyze the dataset withdrawal to conduct inference of the relative risks
#data(withdrawal)
#multiple.RR <- multipletables(data=withdrawal, measure="RR",model="Sarmanov")
#plot(multiple.RR, type="forest", addline=1)
#plot(multiple.RR, type="overlap", select=c(3,8,14,16))
#plot(multiple.RR, type="sidebyside", select=c(3,8,14,16), ylim=c(0,1.2),
#xlim=c(0.4,3))
# Analyze the dataset withdrawal to conduct inference of the risk differences
#data(withdrawal)
#multiple.RD <- multipletables(data=withdrawal, measure="RD",
# model="Sarmanov")
#summary(multiple.RD)
#plot(multiple.RD, type="forest", addline=0)
#plot(multiple.RD, type="overlap", select=c(3,8,14,16))
#plot(multiple.RD, type="sidebyside", select=c(3,8,14,16))
#plot(multiple.RD, type="sidebyside", select=c(3,8,14,16),
# ylim=c(0,6), xlim=c(-0.2,0.4))
``` |

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