ubic.basecode.math.metaanalysis

Class MeanDifferenceMetaAnalysis

java.lang.Object

ubic.basecode.math.metaanalysis.MetaAnalysis

ubic.basecode.math.metaanalysis.MeanDifferenceMetaAnalysis

public class MeanDifferenceMetaAnalysis
extends MetaAnalysis

Meta-analysis methods from chapter 18 of Cooper and Hedges, sections 2.1 and 3.1

These methods use the standardized mean difference statistic d:

 d_i = ( X_i ˆ t - X_i ˆ c ) / s_i
 

where X _i ^t is the mean of the treatment group in the ith study, X _i ^ct is the mean of the control group in the treatment group in the ith study, and s _i is the pooled standard deviation of the two groups. Essentially this is a t statistic.

Author:

pavlidis

Constructor Summary

Constructors

Constructor and Description
MeanDifferenceMetaAnalysis(boolean fixed)

Method Summary

Modifier and Type	Method and Description
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 cvar)
double	run(cern.colt.list.DoubleArrayList effects, cern.colt.list.DoubleArrayList controlSizes, cern.colt.list.DoubleArrayList testSizes)
double	samplingVariance(double d, double nC, double nT) CH eqn 18-7
cern.colt.list.DoubleArrayList	samplingVariances(cern.colt.list.DoubleArrayList effects, cern.colt.list.DoubleArrayList controlSizes, cern.colt.list.DoubleArrayList testSizes) Run eqn 18-7 on a set of effect sizes.

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

MeanDifferenceMetaAnalysis

public MeanDifferenceMetaAnalysis(boolean fixed)

Parameters:

b -

Method Detail

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 cvar)

Parameters:

effects -

cvar - Conditional variances.

Returns:

run

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

samplingVariance

public double samplingVariance(double d,
                               double nC,
                               double nT)

CH eqn 18-7

Parameters:

d - effect size

nC - number of samples in control group

nT - number of samples in test group

Returns:

samplingVariances

public cern.colt.list.DoubleArrayList samplingVariances(cern.colt.list.DoubleArrayList effects,
                                                        cern.colt.list.DoubleArrayList controlSizes,
                                                        cern.colt.list.DoubleArrayList testSizes)

Run eqn 18-7 on a set of effect sizes.

Parameters:

effects -

controlSizes -

testSizes -

Returns: