help midas bclust2binalso see: midas

Title

midas bclust2bin -- Cluster adjustment of 2x2 diagnostic test data

Syntax

midas bclust2bin
tp fp fn tn np
[varlist]
[if exp]
[in range]
[,
id(varlist)
]

Description

midas bclust2bin adjusts 2x2 diagnostic test accuracy counts for
within-study clustering using the design effect (VIF) approach of
Donner and Klar (2000). It is used when studies report clustered data
(e.g., multiple lesions per patient) and inflated cell counts need to be
deflated to an effective sample size before meta-analysis.

The five required variables are, in order:

tp true positives

fp false positives

fn false negatives

tn true negatives

np number of primary sampling units (clusters) per study

The command computes the intraclass correlation coefficient (ICC) and
variance inflation factor (VIF) from the observed counts and cluster sizes,
then creates design-effect-adjusted variables midas_tp, midas_fp,
midas_fn, and midas_tn which can be passed directly to the
midas estimation commands.

Options

id(varlist) specifies one or more study identifier variables.

Saved results

midas bclust2bin creates the following new variables in the dataset:

midas_tp design-effect-adjusted true positives

midas_fp design-effect-adjusted false positives

midas_fn design-effect-adjusted false negatives

midas_tn design-effect-adjusted true negatives

Example

. midas bclust2bin tp fp fn tn np, id(author year)

. midas mle midas_tp midas_fp midas_fn midas_tn, id(author year)

References

Donner A, Klar N. Design and Analysis of Cluster Randomization Trials in Health Research.
Arnold, London, 2000.

Author

Ben A. Dwamena, University of Michigan.

bdwamena@umich.edu

Also see

midas, midas con2bin, midas ord2bin, midas ipd2ad