统计初学小记

peto-prentice广义Wilcoxon检验：

proc lifetest data = xx;

time time * censor(1);*** aval * cnsr(1) ***;

strata 分层因素 / group = trtpn test = peto adjust = dunnett diff = control("2");

*** control 控制，2为对照组，方法为peto，Dunnett法校正***;

run;

Bootstrap重复抽样构造数据集：

proc serveyselect data = xx seed = 20231231 out = dataset method = urs samprate = 1 reps = 500 outhits;

**seed: 随机种子， reps：重复次数***;

strata trtpn;

run;

proc univariate data = newdata;

class trtpn;

var diff; *** diff：中位时间的组间差异***;

output out = ci n = n pctlpts = 2.5, 97.5 patlpre = ci;

run;

Mantel-Haenszel（M-H）检验：

proc freq data = xx;

table 分层因素1 * 分层2 * trtpn * response /cmh2;

run;

协方差分析（ANCOVA）:

*** method 1 ***;

proc glm data = xx;

class trtpn;

model chg = base trtpn / ss3; ***默认ss3，可选ss1，带base是协方差，不带base是直方差***;

lsmeans trtpn; ***lsmeans用于出最小二乘均数***;

run;

*** method 2 ***;

proc anova data = xx;

class trtpn;

model chg = trtpn base trtpn * base;

run;

5. 最小二乘均数：

proc glm data = xx;

class trtpn;

lsmeans trtpn; ***lsmeans用于出最小二乘均数***;

run;

6.非参Wilcoxon检验：

proc npar1way data = xx Wilcoxon DSCF;

class trtpn;

var xxx;

run;

7.Fisher精确检验：|

proc feq data = xx;

table trtpn * aval / exact;

run;

8.Clopper-Pearson确切法：

proc freq data = xx;

by trtpn;

tables response / out = xxx binomial(cl = exact level = '1');

ods output binomialcls = xxxxx;

run;

9.确切CMH检验：

proc logistic data = xx;

class trtpn 分层 / param = ref;

model response = trtpn;

strata 分层;

exact trtpn / extimate = odds;

run;

10.MI填补：

proc mi data = xx seed = nimpute = 100 out = mi;

var strata aval1 aval2;

mcmc chain = muitiple impute = monotone  nbiter = 200                  niter = 200;

by trtpn;

run;

  proc sort data = mi; by _imputation_ trtpn usubjid strata

aval1 aval2; run;

proc mi data = mi seed = nimpute = 1 out = xxx;

class trtpn strata;

by _imputation_;

var trtpn strata aval1 aval2;

monotone reg ( aval2 );

run;

11.卡方检验（x²检验）：

proc freq data = xx;

table trtpn / chisq;

run;

12.Newcombe法：

proc freq data = xx;

tables trtpn * aval / riskdiff(cl = newcombe)

nopercent ncol alpha = 0.1;

by ;

run;

13.Hodges-Lehmann法：

proc npar1way /* hl  alpha = 0.05 */ data = xx;

class trtpn;

var aval;    ***aval是需要检验的变量***;

*exact hl;  ***加上hl表示只输出HL的检验结果***;

output out = xxx hl;

quit;

14.M-N(Miettinen-Nurminen)：

proc freq data = xx;

tables trtpn * response / chisq fisher expected

riskdiff(cl = mn);

*** chisq卡方，fisher：fisher法***;

run;

15.Wald法：

proc freq data = xx;

tables trtpn * aval / riskdiff(cl = wald)

alpha = 0.05 crosslist;

run;

16.K-M和logrank计算P值：

proc lifetest data = xx method = km conftype = linear;

time aval * cnsr(1);

strata strata1 group = trtpn test = logrank;|

***strata1为分层因素***;

quit;

17.Cox风险比例模型计算HR和置信区间：

proc phreg data = xx;

class trtpn(ref = '2'); ***2为对照组***;

model aval * cnsr(1) = trtpn / ties = exact risklimits

/*=pl*/ appha = 0.05 selecion = none;

strata strata1;

hazardratio trtpn / diff = ref;

run;

初步小记，后续更新修正。