summary.multipletables: Summary a specific study of objects 'multipletables'

Description Usage Arguments Value References See Also Examples

View source: R/summary.r

Description

Summary a model of class multipletables fitted by multipletables.

Usage

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      ## S3 method for class 'multipletables'
summary(object,...) 

Arguments

object

an object inheriting from class multipletables.

...

additional arguments; currently none is used.

Value

A list with the following components:

model

the value of model argument.

measure

the value of measure argument.

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 alpha argument.

MLE

a numeric vector of the estimated hyperparameters in the following order: a1, b1, a2, b2, rho.

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.

References

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.

See Also

multipletables plot.multipletables

Examples

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#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))

Example output



mmeta documentation built on May 2, 2019, 6:47 a.m.