dat.higgins2008: Trials on Haloperidol in Schizophrenia

In metadat: Meta-Analysis Datasets

Trials on Haloperidol in Schizophrenia

Description

Results on clinical improvement after therapy from 17 trials evaluating haloperidol in patients with schizophrenia.

Usage

dat.higgins2008

Format

The data frame contains the following columns:

author	character	study label
resp.halo	integer	number of responders (haloperidol group)
fail.halo	integer	number of failures (haloperidol group)
miss.halo	integer	number of missing observations (haloperidol group)
resp.plac	integer	number of responders (placebo group)
fail.plac	integer	number of failures (placebo group)
miss.plac	integer	number of missing observations (placebo group)

Details

Higgins et al. (2008) suggested several imputation methods for the meta-analysis of binary outcomes with missing data. The example data set with 17 trials comes originally from a Cochrane review comparing haloperidol with placebo for the treatment of schizophrenia. While the antipsychotic benefits of haloperidol were identified in the 1950s, trials in this patient population are prone to high proportions of missing outcome data, often due to insufficient compliance with randomized controlled trial protocols.

The outcome is clinical improvement after therapy. For each study, the number of responders, failures, and missing observations are available.

Concepts

psychiatry, odds ratios, missing data

Author(s)

Guido Schwarzer, [e-mail], https://github.com/guido-s/

Source

Higgins, J. P. T., White, I. R., & Wood, A. M. (2008). Imputation methods for missing outcome data in meta-analysis of clinical trials. Clinical Trials, 5(3), 225–239. ⁠https://doi.org/10.1177/1740774508091600⁠

Examples

### Show first five studies
head(dat.higgins2008, 5)

## Not run: 
### Load metasens package
suppressPackageStartupMessages(library(metasens))

### Print odds ratios and confidence limits with three digits
oldset <- settings.meta(digits = 3)

### Conduct common effect meta-analysis of available data
m <- metabin(resp.halo, resp.halo + fail.halo,
  resp.plac, resp.plac + fail.plac,
  data = dat.higgins2008, studlab = author,
  sm = "OR", method = "Inverse", random = FALSE,
  label.e = "Haloperidol", label.c = "Placebo",
  label.left = "Favours placebo",
  label.right = "Favours haloperidol")

### Best case scenario for haloperidol
m.b <- metamiss(m, miss.halo, miss.plac,
  method.miss = "b", small.values = "undesirable")

### Worst case scenario for haloperidol
m.w <- metamiss(m, miss.halo, miss.plac,
  method.miss = "w", small.values = "undesirable")

### Forest plot
m.sens <- metamerge(m, m.b, text.pooled2 = "Best case scenario")
m.sens <- metamerge(m.sens, m.w, text.pooled2 = "Worst case scenario")
forest(m.sens)

## End(Not run)

metadat documentation built on April 29, 2026, 5:10 p.m.