均匀设计数据分析——SPSS190

1、1 .表头选择及因素水平安排巩F表头小封便用表xlx2x3列号D11242120.31224331230.45733124431最后一行均为最高水平组合，舍弃因素表xlx2因素ABC可自行安排因素排布r三因素四水平三因素四水平均匀设计表k1x2x3xlx2x3总剂量110303511060140210220607022012010522533090105330307013044012014044090351652 .数据分析步骤一一SPSS19.0（此例中每组动物数量为6只）2.1 首先：除了标注XI、X2和X3外，最好也分析两两互作的情况如X1*X2等（也可不计算，本例中因为仅3因素，也考察

2、了三因素的互作X1*X2*X3）,最后一列为要分析的对象，本例中为Glucosexlx2k3iPx?xhsJx2Ghicosexlx2x3xl<x2xl,心Ghicose111060140600140084008400014.0313&307090021M21006300012.0121060140m140084008400014.43230307090021M21006300012.0B106014060014008400S400016.53330307090021M21006300013.0141060140600140084008400012.734303070m21002

3、1006300014.0151060140m14008400S400017.03530307090。21M21006300012.0161060140600140084008400018.8363。3070m21M21006300011.0212012010524002100126002520008.941409035360014003150126000114.0222012010524002100126002520009.04240903536001400315012600013.0232012010524002100126002520007.943409035360014003150126

4、000rno2420120105240021001260025200011.244409035360014003150126000rno2520120105240021001260025200010.445409035360014003150126000rbo262012010524002100126002520009.04640903536001400315012600015.0可见本例中，不同颜色标记为四个组别，每组各6只动物，如试验中间有缺失，则删除即可；2.2启动SPSS19.0,定义变量等，如下匚名梆类型建标签值缺失列对齐度量标准匚角色1X1数值(N)20无无3李左£名义(

5、附、输入2X2散值(N)20无无3布左名名义网、输入3X3数值(N)20无无5室左.名义(附、输入4X1xX2数值(N)5C无无5重左A名义网、输入5X1xX3数值50无无5手左£名义、输入X2xX3散值(N)8C无无5室左R名义(N)、输入7X1xX2zX3散值时S0无无1言右名义网、输入8Glucose数值(N)81mmol/L无无至后£名义网、输入注：类型一栏选择数值型按照图2及图3输入各数据，见图4(共24个，省去部分)X1X2X3X1xX2X1xX3X2xX3X1xX2xX3Glucose1106口140600uoo8400B400014.021060140600

6、140084008400014.431060140600uoo84008400016.5410601406001400840Q8400012.751060140600UOO84008400017.06n106014060014008400840001B.81二20121002400210012600252000893201210024002100126002520009.09201210024002100126002620007.9102012100240021001260026200011211n2012100240021001260025200010.4122012100240021001

7、26002520009013303070900210021006300012.0un303070900210021006300012.015口303070900210021006300013.016303070900210021006300014.02.3选择执行分析一回归一线性(图5)转换CD分析造）宜销此图形&）实用程序乜）窗口国）"助X1xX3X2140084C140084C140084C140084C140084C140。84C?10012E310012E“0012E>10012E?10012E“0口12E310021C”0021C?10021C”0021c?1

8、0021C210021C140031E140031EtdAflH4rri报告描述获计表（T）比较均值坦）一般当性模型叁）>广义线性模型>潟合模型凶相关值）回归®+对数线性模型9）神经网络分类（E）降雄度量（S）>非参数检幼型）+顼测生存函敷岁重响应Q）目喊失值分析直L多重归因CD复杂抽样&）质量控制拽）ROC曲线圉区）同自动线性建模后）麻线性曲线估计（白回部分晟小平方二元Logistic.赛多项Logistic.H有序MProbit.则非线性（凶机重估计）两阶晶小二重法R）曷佳尺度（CATREGL然后进入图6界面，将被分析的对象（本例Glucose）调入因变

9、量，其他调入自变量，万法调整为逐步，然后确定X.1K2X3X1X,1X2X.1ftlBl玷mmolfl-(Glucose团支!:，方法也：谢fwsIwup)iImaIIJLj啮说；，2.4然后SPSS输出报告本例中，数据为任意输入，可见如不考虑三各因素的互作，则可只用Glucose=22.117-0.005X1*X3说明X2不是主要因素，若为了得到最小的Glucose,则根据上述公式，X1*X3则应最大，则X1=30,X3=140;VariablesEntmreU/RBmovEd9ModelVariablesEnteredVariablesRgmo*edMethod12X1xX3X1xX2xX

10、3Stepwise(Orrisria.Probability-oF-W-entei<=.050,Frababiliiy-oF-to-removs>=.100).Stepwise(Criteria:Probability-olMounter".050,Probability-F-tfl-remove>=.100).a.DependentVariable:mmol/LModelSumofSquaresatSquareF汕1RegressionResidualTotalB4.27585783170,15812223643753.39921.639,0002Rsgressi

11、ioruResidualTotal116.5C553594170.15E231二58.2822.55222.037.oocfcANnVA08Prsdictors:(Constanfi,X1毋(3bPredlctors:(Cansta,X1)0C3bXicDependentvariablemmoULCceffitbeots5blodeiRRSquareAdjusledRSquareStd.ErrorofttieEstimate17041,496,4731.97462.B28bB8565515975ModelSummaryaPrsdiclars;(Constant),X1xX3b.Predictors:(Constant),XlkXS,X1霖榻(3ModelUn&tenciardteedCoefficientsStandardiizdCoemcientstsigBSid.ErrorBetai(Constant22.TT72万5510761000X1)