spearman与person相关分析对比.ppt

,Spearman与Pearson,汇报人：屠星月,内容,Spearman相关系数的含义Spearman相关分析的特点Spearman与Pearson相关分析的对比结果的解释对我的研究数据的适用性,一,Spearman相关系数的含义,Spearmanrank-ordercorrelationcoefficient,两个连续或等级/秩变量之间的单调相关（monotoneassociation）关系。单调函数描述两个变量之间的关系的程度（howwelltherelationshipbetweentwovariablescanbedescribedusingamonotonicfunction）Pearson相关系数的一个特例（系数计算中的X,Y被其秩代替）：,RxandRyaretheranksofthexandyvariables,respectively,isthesquareofthedifferencebetweenthecorrespondingranksofxiandyi,andnisthenumberobservations.,二,Spearman相关分析的特点,不对变量的分布做假设：非参数（自由分布）可用于等级数据（ordinaldata：Themostfundamentalrequisiteistobeabletomeasureourobservedcorrespondencebyaplainnumericalsymbol）当数据分布导致，pearson相关系数不适用或者产生误导的使用。whenthedistributionofdatamakesPearsonscorrelationcoefficientundesirableormisleading当数据为定性的变量，或者含有异常值时尤其适用。,三,Spearman与Pearson相关分析的对比,三,Spearman与Pearson相关分析的对比,三,Spearman与Pearson相关分析的对比,1.对同样的数据，Spearman相关统计相关，而pearson可能显著也可能不显著thesignificanceofSpearmanscorrelationcanleadtothesignificanceornon-significanceofPearsonscorrelationcoefficientevenforbigsetsofdata2.对同样的数据，二者所得的相关系数符号有可能不一样（ItispossibletomeetasituationwherePearsonscoefficientisnegativewhileSpearmanscoefficientispositive.）3.注意：确保不要针对两个变量的相关强度，对spearman相关系数过度解释MakesurenottooverinterpretSpearmansrankcorrelationcoefficientasasignificantmeasureofthestrengthoftheassociationsbetweentwovariables.,四,结果的解释,四,结果的解释,r与P值,呈现分析结果时应当包含的信息,当统计显著，但相关系数不大，则有可能是其他变量的影响,四,结果的解释,r的大小,BenedictK，TheCorrelationCoefficient-ExplainedinThreeSteps，,四,结果的解释,六,参考文献,Sullivan,G.M.andR.Feinn(2012).Usingeffectsize-orwhythePvalueisnotenough.Journalofgraduatemedicaleducation4(3):279-282.Support,M.E.AcomparisonofthePearsonandSpearmancorrelationmethods.“Hauke,J.andT.Kossowski(2011).ComparisonofvaluesofPearsonsandSpearmanscorrelationcoefficientsonthesamesetsofdata.Quaestionesgeographicae30(2):87-93.Martinez-Abrain,A.(2008).Statisticalsignificanceandbiologicalrelevance:Acallforamorecautiousinterpretationofresultsinecology.actaoecologica34