ubic.basecode.math.metaanalysis

Class CorrelationEffectMetaAnalysis

java.lang.Object

ubic.basecode.math.metaanalysis.MetaAnalysis

ubic.basecode.math.metaanalysis.CorrelationEffectMetaAnalysis

public class CorrelationEffectMetaAnalysis
extends MetaAnalysis

Implementation of meta-analysis of correlations along the lines of chapter 18 of Cooper and Hedges, "Handbook of Research Synthesis". Both fixed and random effects models are supported, with z-transformed or untransformed correlations.

Author:

pavlidis

Constructor Summary

Constructors

Constructor and Description
CorrelationEffectMetaAnalysis()
CorrelationEffectMetaAnalysis(boolean fixed, boolean transform)

Method Summary

Modifier and Type	Method and Description
protected double	fisherTransformedSamplingVariance(double sampleSize) Equation 18-8 from CH.
protected cern.colt.list.DoubleArrayList	fisherTransformedSamplingVariances(cern.colt.list.DoubleArrayList sampleSizes) Run equation CH 18-8 on a list of sample sizes.
double	getBsv()
double	getE()
double	getN()
double	getP()
double	getQ()
double	getV()
double	getZ()
double	run(cern.colt.list.DoubleArrayList effects, cern.colt.list.DoubleArrayList sampleSizes) Following CH section 2.2.
protected static double	samplingVariance(double r, double numsamples) Equation 18-10 from CH.
protected cern.colt.list.DoubleArrayList	samplingVariances(cern.colt.list.DoubleArrayList effectSizes, cern.colt.list.DoubleArrayList sampleSizes) Run equation CH 18-10 on a list of sample sizes and effects.
void	setFixed(boolean fixed)
void	setTransform(boolean transform)

Methods inherited from class ubic.basecode.math.metaanalysis.MetaAnalysis

fisherCombineLogPvalues, fisherCombinePvalues, metaFEWeights, metaRESampleVariance, metaREVariance, metaREWeights, metaVariance, metaVariance, metaZscore, qStatistic, qTest, weightedMean, weightedMean

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

CorrelationEffectMetaAnalysis

public CorrelationEffectMetaAnalysis()

CorrelationEffectMetaAnalysis

public CorrelationEffectMetaAnalysis(boolean fixed,
                                     boolean transform)

Method Detail

samplingVariance

protected static double samplingVariance(double r,
                                         double numsamples)

Equation 18-10 from CH. For untransformed correlations.

 v_i = ( 1 - r_i ˆ 2 ) ˆ 2 / ( n_i - 1 )
 

I added a regularization to this, so that we don't get ridiculous variances when correlations are close to 1 (this happens). If the correlation is very close to 1 (or -1), we fudge it to be a value less close to 1 (e.g., 0.999)

Parameters:

r -

n -

Returns:

getBsv

public double getBsv()

getE

public double getE()

getN

public double getN()

getP

public double getP()

getQ

public double getQ()

getV

public double getV()

getZ

public double getZ()

run

public double run(cern.colt.list.DoubleArrayList effects,
                  cern.colt.list.DoubleArrayList sampleSizes)

Following CH section 2.2.

There are four possible cases (for now):

1. Fixed effects, Z-transformed. Weights are computed using CH eqns 18-8 and 18-3
2. Fixed effects, untransformed. Weights are computed using CH eqns 18-10 and 18-3
3. Random effects, Z-transformed. Weights are computed using CH eqns 18-20, 18-8 with 18-3
4. Random effects, untransformed. Weights are computed using CH eqns 18-10, 18-20, 18-24.

The default is untransformed, fixed effects.

Parameters:

correlations - - NOT fisher transformed. This routine takes care of that.

sampleSizes -

Returns:

p-value. The p-value is also stored in the field p.

setFixed

public void setFixed(boolean fixed)

setTransform

public void setTransform(boolean transform)

fisherTransformedSamplingVariance

protected double fisherTransformedSamplingVariance(double sampleSize)

Equation 18-8 from CH. For z-transformed correlations.

 v_i = 1 / ( n_i - 3 )
 

Parameters:

n -

Returns:

fisherTransformedSamplingVariances

protected cern.colt.list.DoubleArrayList fisherTransformedSamplingVariances(cern.colt.list.DoubleArrayList sampleSizes)

Run equation CH 18-8 on a list of sample sizes.

Parameters:

sampleSizes -

Returns:

samplingVariances

protected cern.colt.list.DoubleArrayList samplingVariances(cern.colt.list.DoubleArrayList effectSizes,
                                                           cern.colt.list.DoubleArrayList sampleSizes)

Run equation CH 18-10 on a list of sample sizes and effects.

Parameters:

effectSizes -

sampleSizes -

Returns:

See Also:

samplingVariance