metafor: dat.collins1985a – R documentation

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dat.collins1985a

Studies on the Treatment of Upper Gastrointestinal Bleeding by a Histamine H2 Antagonist

Description

Results from studies examining the effectiveness of histamine H2 antagonists (cimetidine or ranitidine) in treating patients with acute upper gastrointestinal hemorrhage.

Usage

dat.collins1985a

Format

The data frame contains the following columns:

id	`numeric`	study number
trial	`character`	first author of trial
year	`numeric`	year of publication
ref	`numeric`	reference number
trt	`character`	C = cimetidine, R = ranitidine
ctrl	`character`	P = placebo, AA = antacids, UT = usual treatment
nti	`numeric`	number of patients in treatment group
b.xti	`numeric`	number of patients in treatment group with persistent or recurrent bleedings
o.xti	`numeric`	number of patients in treatment group in need of operation
d.xti	`numeric`	number of patients in treatment group that died
nci	`numeric`	number of patients in control group
b.xci	`numeric`	number of patients in control group with persistent or recurrent bleedings
o.xci	`numeric`	number of patients in control group in need of operation
d.xci	`numeric`	number of patients in control group that died

Details

The data were obtained from Tables 1 and 2 in Collins and Langman (1985). The authors used Peto's (one-step) method for meta-analyzing the 27 trials. This approach is implemented in the rma.peto function. Using the same dataset, van Houwelingen, Zwinderman, and Stijnen (1993) describe some alternative approaches for analyzing these data, including fixed and random-effects conditional logistic models. Those are implemented in the rma.glmm function.

Source

Collins, R., & Langman, M. (1985). Treatment with histamine H2 antagonists in acute upper gastrointestinal hemorrhage. New England Journal of Medicine, 313, 660–666.

References

van Houwelingen, H. C., Zwinderman, K. H., & Stijnen, T. (1993). A bivariate approach to meta-analysis. Statistics in Medicine, 12, 2273–2284.

Examples

### copy data into 'dat' and examine data
dat <- dat.collins1985a
dat

### meta-analysis of log ORs using Peto's method (outcome: persistent or recurrent bleedings)
res <- rma.peto(ai=b.xti, n1i=nti, ci=b.xci, n2i=nci, data=dat)
print(res, digits=2)

## Not run: 
### meta-analysis of log ORs using a conditional logistic regression model (FE model)
res <- rma.glmm(measure="OR", ai=b.xti, n1i=nti, ci=b.xci, n2i=nci, data=dat,
                model="CM.EL", method="FE")
summary(res)
predict(res, transf=exp, digits=2)

### plot the likelihoods of the odds ratios
llplot(measure="OR", ai=b.xti, n1i=nti, ci=b.xci, n2i=nci, data=dat,
       lwd=1, refline=NA, xlim=c(-4,4), drop00=FALSE)

### meta-analysis of log odds ratios using a conditional logistic regression model (RE model)
res <- rma.glmm(measure="OR", ai=b.xti, n1i=nti, ci=b.xci, n2i=nci, data=dat,
                model="CM.EL", method="ML")
summary(res)
predict(res, transf=exp, digits=2)

## End(Not run)

### meta-analysis of log ORs using Peto's method (outcome: need for surgery)
res <- rma.peto(ai=o.xti, n1i=nti, ci=o.xci, n2i=nci, data=dat)
print(res, digits=2)

### meta-analysis of log ORs using Peto's method (outcome: death)
res <- rma.peto(ai=d.xti, n1i=nti, ci=d.xci, n2i=nci, data=dat)
print(res, digits=2)

metafor

Meta-Analysis Package for R

v2.4-0

GPL (>= 2)

Authors

Wolfgang Viechtbauer [aut, cre] (<https://orcid.org/0000-0003-3463-4063>)

Initial release

2020-03-19