CS计算机代考程序代写 libname bis ‘c:\BIS679A\’;

libname bis ‘c:\BIS679A\’;
data bis.lead; input id group $ lead0 lead1 lead4 lead6; datalines;
1 P 30.8 26.9 25.8 23.8
2 A 26.5 14.8 19.5 21.0
3 A 25.8 23.0 19.1 23.2
4 P 24.7 24.5 22.0 22.5
5 A 20.4 2.8 3.2 9.4
6 A 20.4 5.4 4.5 11.9
7 P 28.6 20.8 19.2 18.4
8 P 33.7 31.6 28.5 25.1
9 P 19.7 14.9 15.3 14.7
10 P 31.1 31.2 29.2 30.1
11 P 19.8 17.5 20.5 27.5
12 A 24.8 23.1 24.6 30.9
13 P 21.4 26.3 19.5 19.0
14 A 27.9 6.3 18.5 16.3
15 P 21.1 20.3 18.4 20.8
16 P 20.6 23.9 19.0 17.0
17 P 24.0 16.7 21.7 20.3
18 P 37.6 33.7 34.4 31.4
19 A 35.3 25.5 26.3 30.3
20 A 28.6 15.8 22.9 25.9
21 P 31.9 27.9 27.3 34.2
22 A 29.6 15.8 23.7 23.4
23 A 21.5 6.5 7.1 16.0
24 P 26.2 26.8 25.3 24.8
25 A 21.8 12.0 16.8 19.2
26 A 23.0 4.2 4.0 16.2
27 A 22.2 11.5 9.5 14.5
28 P 20.5 21.1 17.4 21.1
29 A 25.0 3.9 12.8 12.7
30 P 33.3 26.2 34.0 28.2
31 A 26.0 21.4 21.0 22.4
32 A 19.7 13.2 14.6 11.6
33 P 27.9 21.6 23.6 27.7
34 P 24.7 21.2 22.9 21.9
35 P 28.8 26.4 23.8 22.0
36 A 29.6 17.5 21.0 24.2
37 P 32.0 30.2 30.2 27.5
38 P 21.8 19.3 16.4 17.6
39 A 24.4 16.4 11.6 16.6
40 A 33.7 14.9 14.5 63.9
41 P 24.9 20.9 22.2 19.8
42 P 19.8 18.9 18.9 15.5
43 A 26.7 6.4 5.1 15.1
44 A 26.8 20.4 19.3 23.8
45 A 20.2 10.6 9.0 16.0
46 P 35.4 30.4 26.5 28.1
47 P 25.3 23.9 22.2 27.2
48 A 20.2 17.5 17.4 18.6
49 A 24.5 10.0 15.6 15.2
50 P 20.3 21.0 16.7 13.5
51 P 20.4 17.2 15.9 17.7
52 P 24.1 20.1 17.9 18.7
53 A 27.1 14.9 18.1 21.3
54 A 34.7 39.0 28.8 34.7
55 P 28.5 32.6 27.5 22.8
56 P 26.6 22.4 21.8 21.0
57 A 24.5 5.1 8.2 23.6
58 P 20.5 17.5 19.6 18.4
59 P 25.2 25.1 23.4 22.2
60 P 34.7 39.5 38.6 43.3
61 P 30.3 29.4 33.1 28.4
62 P 26.6 25.3 25.1 27.9
63 P 20.7 19.3 21.9 21.8
64 A 27.7 4.0 4.2 11.7
65 A 24.3 24.3 18.4 27.8
66 A 36.6 23.3 40.4 39.3
67 P 28.9 28.9 32.8 31.8
68 A 34.0 10.7 12.6 21.2
69 A 32.6 19.0 16.3 18.6
70 A 29.2 9.2 8.3 18.4
71 A 26.4 15.3 24.6 32.4
72 A 21.8 10.6 14.4 18.7
73 P 27.2 28.5 35.0 30.5
74 P 22.4 22.0 19.1 18.7
75 P 32.5 25.1 27.8 27.3
76 P 24.9 23.6 21.2 21.1
77 P 24.6 25.0 21.7 23.9
78 P 23.1 20.9 21.7 19.9
79 A 21.1 5.6 7.3 12.3
80 P 25.8 21.9 23.6 24.8
81 P 30.0 27.6 24.0 23.7
82 A 22.1 21.0 8.6 24.6
83 P 20.0 22.7 21.2 20.5
84 P 38.1 40.8 38.0 32.7
85 A 28.9 12.5 16.7 22.2
86 P 25.1 28.1 27.5 24.8
87 A 19.8 11.6 13.0 23.1
88 P 22.1 21.1 21.5 20.6
89 A 23.5 7.9 12.4 18.9
90 A 29.1 16.8 15.1 18.8
91 A 30.3 3.5 3.0 11.5
92 P 25.4 24.3 22.7 20.1
93 A 30.6 28.2 27.0 25.5
94 A 22.4 7.1 17.2 18.7
95 A 31.2 10.8 19.8 22.2
96 A 31.4 3.9 7.0 17.8
97 A 41.1 15.1 10.9 27.1
98 A 29.4 22.1 25.3 4.1
99 A 21.9 7.6 10.8 13.0
100 A 20.7 8.1 25.7 12.3
run;

title1 Subsample (N=50) of data on Blood Lead Levels from the Placebo Group;
title2 Treatment of Lead Exposed Children (TLC) Trial;

proc corr cov plots=matrix;
var lead0 lead1 lead4 lead6;
where group=’P’;
run;
data bis.placebo; set bis.lead; if group=’P’; run;

title1 Subsample (N=50) of data on Blood Lead Levels from the Succimer Group;
title2 Treatment of Lead Exposed Children (TLC) Trial;

proc corr data=bis.lead cov plots=matrix;
var lead0 lead1 lead4 lead6;
where group=’A’;
run;
data bis.succimer; set bis.lead; if group=’A’; run;

proc ttest data = bis.succimer; paired lead0 * lead1; run;

data tlc; set bis.lead;
y=lead0; time=0; output;
y=lead1; time=1; output;
y=lead4; time=4; output;
y=lead6; time=6; output;
drop lead0 lead1 lead4 lead6;
/*if (id ne 197);*/
proc print; run;
***********************************************;

* Removing outlier: Subject ID = 197 *;

***********************************************;

data succimer;
set tlc;
if (group = ‘A’);

proc sort;
by id time;
run;

goptions reset = all;
symbol1 value=circle color=black interpol = join repeat = 50;
axis1 order =(0 to 6 by 1) label=(‘Time (in Days)’);
axis2 order =(0 to 70 by 10) label = (angle=90 ‘Blood Lead Levels (mcg/dL)’);

title1 Time Plot, with Joined Line Segments, of Blood Lead Levels in the Succimer Group;
title2 Treatment of Lead Exposed Children (TLC) Trial;

proc gplot data = succimer;
plot y*time = id / haxis = axis1 vaxis = axis2 nolegend;
run;

data twotime; set tlc; if (group =’A’); if time le 1; run;
proc ttest; class time; var y; run;

data placebo;
set tlc;
if (group = ‘P’);

proc sort;
by id time;
run;

goptions reset = all;
symbol1 value=circle color=black interpol = join repeat = 50;
axis1 order =(0 to 6 by 1) label=(‘Time (in Days)’);
axis2 order =(0 to 70 by 10) label = (angle=90 ‘Blood Lead Levels (mcg/dL)’);

title1 Time Plot, with Joined Line Segments, of Blood Lead Levels in the Placebo Group;
title2 Treatment of Lead Exposed Children (TLC) Trial;

proc gplot data = placebo;
plot y*time = id / haxis = axis1 vaxis = axis2 nolegend;
run;

proc sgplot data=placebo;
series x=time y=y /group=id; run;

proc means data=tlc n mean nway;
var y;
class time group;
output out=leadmean mean=mean;
run;

goptions reset = all;

symbol1 value=circle color=black interpol = join;
symbol2 value=triangle color=red interpol = join;
axis1 order =(0 to 6 by 1) label=(‘Time (in Days)’);
axis2 order =(10 to 30 by 5) label = (angle=90 ‘Blood Lead Levels (mcg/dL)’);

title1 Time Plot of Mean Blood Lead Levels in the Placebo and Succimer Groups;
title2 Treatment of Lead Exposed Children (TLC) Trial;

proc gplot data=leadmean;
plot mean*time=group / haxis = axis1 vaxis = axis2;
run;

/*What is different about using Proc GLM versus Proc Mixed?
GLM assumes that all of the observations are
independent and with homogeneous variance while MIXEd accounts for
the covariance among repeated measures*/

PROC GLM DATA=succimer;
CLASS time;
MODEL y = time /SOLUTION;
ESTIMATE ‘Week 6 – Week 0’ time -1 0 0 1;
RUN;

PROC MIXED DATA=succimer;
CLASS id time;
MODEL y = time /S CHISQ;
REPEATED time /TYPE=UN SUBJECT=id R;
CONTRAST ‘Week 6 – Week 0’
time -1 0 0 1 / CHISQ; run;

/*lets look at both groups now*/
PROC MIXED data=tlc ORDER=DATA;
CLASS id group time;
MODEL y=group time group*time /S CHISQ;
REPEATED time / TYPE=UN SUBJECT=id R RCORR;run;