SAS统计分析范例(20091110).doc

SAS统计分析程序范例proc iml;t=11.1 13.3 20.2;m3=orpol(t,2);print m3;run;Data aa; Input group $ level $ value ;Cards;B11.920279933B11.994526316B12.362389023B12.276282528B12.261029412B21.962594458B21.825117986B21.881757169B21.782291667B21.909411765B21.88030751B22.154036458B31.846367656B31.904365904B31.787766878B31.779214781B31.729896907B31.823794997A11.979061785A11.752841868A11.754926511A11.882359081A12.103314572A12.13045085A11.820079863A21.846532218A21.878964401A21.678232216A21.704280557A21.673333333A21.920341258A31.65288075A31.571456217A31.564559216A31.663129252A31.671637816A31.747802787;run;一.数据的正态性检验A.SAS统计分析程序-title 三种不同添加剂饲喂动物后尿中氨氮的排出量;options ps=500 ls=100; proc import datafile=D: 三种不同添加剂饲喂动物后尿中氨氮的排出量.xls out=a dbms=excel replace; run; data ax; set a;proc print;proc UNIVARIATE normal; var x; by group;run;-B.SAS统计分析相关数据文件三种不同添加剂饲喂动物后尿中氨氮的排出量.xlsgroupx130127135135129133132136126141133131243245253244251253254237247257248242382366366386356352376383372373359353注：数据文件中group为三种不同的添加剂处理，x为动物尿中氨氮排出量。C.SAS程序运行后输出的主要结果-group=1 Tests for Normality Test -Statistic- -p Value- Shapiro-Wilk W 0.973131 Pr D 0.1500 Cramer-von Mises W-Sq 0.020807 Pr W-Sq 0.2500 Anderson-Darling A-Sq 0.171307 Pr A-Sq 0.2500group=2 Tests for Normality Test -Statistic- -p Value- Shapiro-Wilk W 0.970828 Pr D 0.1500 Cramer-von Mises W-Sq 0.031749 Pr W-Sq 0.2500 Anderson-Darling A-Sq 0.205907 Pr A-Sq 0.2500group=3 Tests for Normality Test -Statistic- -p Value- Shapiro-Wilk W 0.937086 Pr D 0.1500 Cramer-von Mises W-Sq 0.0366 Pr W-Sq 0.2500 Anderson-Darling A-Sq 0.271405 Pr A-Sq 0.2500-结果说明：由于Shapiro-Wilk检验的结果P均大于0.05，故判定三组数据均来自正态分布总体。附录：关于正态性检验说明在SAS正态分布检验中，当n2000时，应选用Shapiro-Wilk检验，当W值越接近于1，提示数据符合正态分布；当W值偏离1，提示数据不符合正态分布。当n2000时，应选用Kolmogorov-Smirnov检验，D值越大，P值越小，表示数据不符合正态分布，反之，D值越小，P值越大，提示数据符合正态分布。（SAS软件标准）二.数据的方差同质性检验及数据转化2.1数据的方差同质性检验A.SAS统计分析程序-Title 三种不同添加剂饲喂动物后尿中氨氮的排出量;options ps=500 ls=100; proc import datafile=D:三种不同添加剂饲喂动物后尿中氨氮的排出量.xls out=a dbms=excel replace; run; quit;data aa; set a;proc means; var x; by group;run;proc means noprint data=aa; var x; by group;output out=mx1 css=ss N=N std=s;run;data mx2;set mx1;f=N-1;u=1/f;_type_=1;logs=2*f*log(s);run;proc means noprint data=mx2;var ss N f u logs _type_;output out=mx3 sum=t_ss t_N t_f t_u t_logs k;data result;set mx3;sc2=t_ss/t_f;fz=t_f*log(sc2)-t_logs;fm=1+1/3/(k-1)*(t_u-1/t_f);df=k-1;chisqr=fz/fm;prob=1-probchi(chisqr,df);proc print noobs;var chisqr df prob;run;-B.SAS统计分析相关数据文件 与上表相同(三种不同添加剂饲喂动物后尿中氨氮的排出量.xls).C.SAS程序运行后输出的主要结果- group=1 - Analysis Variable : x Mean Std Dev Std Error 32.3333333 4.1633320 1.2018504- group=2 - Analysis Variable : x Mean Std Dev Std Error 47.8333333 5.9058266 1.7048653- group=3 - Analysis Variable : x Mean Std Dev Std Error 68.6666667 11.9036536 3.4362888- chisqr df prob 12.1390 2 .002312362-结果说明：P=0.00230.05，表明三组数据的方差异质。通过比较发现，均数较大的组，其标准差也较大，标准差与均数之间存在某种关系，故需要对原始数据进行对数转换。附录：常见的数据转换有四种 平方根转换 适用于总体呈泊松分布的资料。 对数转换 各组数据的标准差或全距与其平均数大体成比例的资料。 反正弦转换 适用于如发病率、感染率、病死率等服从二项分布的资料。 BOX-COX转换 模型残差不符合正态分布。2.2 数据的方差异质时数据的转换A.SAS统计分析程序-Title 三种不同添加剂对动物尿中氨氮排出量的影响;options ps=500 ls=100; data aa;input group x;x=log10(x/10);cards;130127135;proc UNIVARIATE normal; var x; by group;proc means; var x; by group;run;proc means noprint data=aa; var x; by group;output out=mx1 css=ss N=N std=s;run;data mx2;set mx1;f=N-1;u=1/f;_type_=1;logs=2*f*log(s);run;proc means noprint data=mx2;var ss N f u logs _type_;output out=mx3 sum=t_ss t_N t_f t_u t_logs k;data result;set mx3;sc2=t_ss/t_f;fz=t_f*log(sc2)-t_logs;fm=1+1/3/(k-1)*(t_u-1/t_f);df=k-1;chisqr=fz/fm;prob=1-probchi(chisqr,df);proc print noobs;var chisqr df prob;run;-B.SAS程序运行后输出的主要结果-group=1 Analysis Variable : x N Mean Std Dev Minimum Maximum 12 0.5063849 0.0555546 0.4149733 0.6127839 Tests for Normality Test -Statistic- -p Value- Shapiro-Wilk W 0.98154 Pr D 0.1500 Cramer-von Mises W-Sq 0.020551 Pr W-Sq 0.2500 Anderson-Darling A-Sq 0.154062 Pr A-Sq 0.2500group=2 Analysis Variable : x N Mean Std Dev Minimum Maximum 12 0.6766095 0.0548112 0.5682017 0.7558749 Tests for Normality Test -Statistic- -p Value- Shapiro-Wilk W 0.963895 Pr D 0.1500 Cramer-von Mises W-Sq 0.031012 Pr W-Sq 0.2500 Anderson-Darling A-Sq 0.220164 Pr A-Sq 0.2500group=3 Analysis Variable : x N Mean Std Dev Minimum Maximum 12 0.8306055 0.0768102 0.7160033 0.9344985 Tests for Normality Test -Statistic- -p Value- Shapiro-Wilk W 0.93177 Pr D 0.1500 Cramer-von Mises W-Sq 0.042693 Pr W-Sq 0.2500 Anderson-Darling A-Sq 0.299649 Pr A-Sq 0.2500 -chisqr df prob 1.63401 2 0.44175-结果说明：数据经转换后经检验数据符合正态分布，方差同质性检验的结果表明P=0.441750.05，三组数据的方差同质。可以将转换后的新变量x按照group分组进行单因素方差分析。三.两处理均数间的差异显著性检验（t检验）A.SAS统计分析程序-Title 两种不同饲料添加剂对小猪增重的影响;Options ps=100 ls=100; Data bodywt;Input trt bodywt;Cards;1 13.51 15.8 1 15.3 1 14.2 1 11.0 1 16.1 1 17.2 2 15.3 2 11.0 2 15.7 2 12.3 2 10.8 2 12.0 2 9.8 ; Proc print;Proc means mean min max std; by trt;Proc ttest; class trt; var bodywt; Run;-B.SAS程序运行后输出的主要结果- Statistics Lower CL Upper CL Lower CL Upper CLVariable trt N Mean Mean Mean Std Dev Std Dev Std Dev Std Err bodywt 1 7 12.835 14.729 16.622 1.3194 2.0475 4.5088 0.7739 bodywt 2 7 10.321 12.414 14.508 1.4588 2.2638 4.985 0.8556 bodywt Diff (1-2) -0.199 2.3143 4.828 1.5477 2.1584 3.5629 1.1537 T-Tests Variable Method Variances DF t Value Pr |t| bodywt Pooled Equal 12 2.01 0.0679 bodywt Satterthwaite Unequal 11.9 2.01 0.0682 Equality of Variances Variable Method Num DF Den DF F Value Pr F bodywt Folded F 6 6 1.22 0.8136-结果说明：在数据正态分布、方差同质的情况下，P=0.06790.10，判定两种添加剂对小猪增重有显著影响。四. 方差分析及平均数间的差异显著性检验（F检验）4.1 完全随机设计的方差分析及均数间的差异显著性LSD检验（有缺省数据）A.SAS统计分析程序-Title 不同锰源和锰水平对肉鸡心脏锰含量的影响;options ps=500 ls=100; proc import datafile=D:不同锰源和锰水平对肉鸡心脏锰含量的影响.xls out=a dbms=excel replace; run; quit;data ax; set a; proc print; proc sort; by source level; proc means mean min max std; by source level; run; proc glm; class source level; model XMN =source level source*level/ss1 ss2 ss3 ss4; means source level /lsd;lsmeans source level source*level/stderr pdiff tdiff; run; -B.SAS统计分析相关数据文件不同锰源和锰水平对肉鸡心脏锰含量的影响.xlsSOURCELEVELGROUPXMNMnSO4010.389MnSO4010.385MnSO4010.401MnSO4010.415MnSO4010.464MnSO4010.536MnSO401.MnSO4010.578Mn-AAA010.389Mn-AAA010.385Mn-AAA010.401Mn-AAA010.415Mn-AAA010.464Mn-AAA010.536Mn-AAA01.Mn-AAA010.578Mn-AAB010.389Mn-AAB010.385Mn-AAB010.401Mn-AAB010.415Mn-AAB010.464Mn-AAB010.536Mn-AAB01.Mn-AAB010.578MnSO410020.429MnSO410020.411MnSO410020.596MnSO410020.421MnSO410020.483MnSO410020.735MnSO410020.372MnSO410020.424Mn-AAA10040.414Mn-AAA10040.393Mn-AAA10040.455Mn-AAA10040.417Mn-AAA10040.46Mn-AAA10040.687Mn-AAA10040.618Mn-AAA10040.611Mn-AAB10060.418Mn-AAB10060.334Mn-AAB10060.755Mn-AAB10060.496Mn-AAB10060.445Mn-AAB10060.536Mn-AAB10060.458Mn-AAB10060.584MnSO420030.402MnSO420030.534MnSO420030.397MnSO420030.449MnSO420030.451MnSO420030.473MnSO420030.685MnSO420030.498Mn-AAA20050.414Mn-AAA20050.633Mn-AAA20050.398Mn-AAA20050.448Mn-AAA20050.43Mn-AAA20050.664Mn-AAA20050.466Mn-AAA20050.499Mn-AAB20070.476Mn-AAB20070.492Mn-AAB20070.367Mn-AAB20070.475Mn-AAB20070.433Mn-AAB20070.645Mn-AAB2007.Mn-AAB20070.505 说明：数据文件中如果数据缺失，需用.代替。SOURCE表示三种不同的锰源，LEVEL表示锰源的不同添加水平，XMN表示心肌锰含量。C.SAS程序运行后输出的主要结果- The GLM Procedure Class Level Information Class Levels Values source 3 A B C LEVEL 3 0 100 200 Number of observations 72NOTE: Due to missing values, only 68 observations can be used in this analysis. The GLM ProcedureDependent Variable: XMN XMN Sum of Source DF Squares Mean Square F Value Pr F Model 8 0.14391610 0.01798951 1.99 0.0634 Error 59 0.53325184 0.00903817 Corrected Total 67 0.67716794 R-Square Coeff Var Root MSE XMN Mean 0.212526 20.39984 0.095069 0.466029 Source DF Type I SS Mean Square F Value Pr F source 2 0.01588542 0.00794271 0.88 0.4206 LEVEL 2 0.11429870 0.05714935 6.32 0.0033 source*LEVEL 4 0.01373198 0.00343299 0.38 0.8222 Source DF Type II SS Mean Square F Value Pr F source 2 0.01576879 0.00788439 0.87 0.4233 LEVEL 2 0.11429870 0.05714935 6.32 0.0033 source*LEVEL 4 0.01373198 0.00343299 0.38 0.8222 Source DF Type III SS Mean Square F Value Pr F source 2 0.01752800 0.00876400 0.97 0.3852 LEVEL 2 0.11421065 0.05710533 6.32 0.0033 source*LEVEL 4 0.01373198 0.00343299 0.38 0.8222 Source DF Type IV SS Mean Square F Value Pr F source 2 0.01752800 0.00876400 0.97 0.3852 LEVEL 2 0.11421065 0.05710533 6.32 0.0033 source*LEVEL 4 0.01373198 0.00343299 0.38 0.8222 The GLM Procedure t Tests (LS