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The data files can be downloaded from http://rem.ph.ucla.edu/~rob/mld/data.html .Table 5.1, page 121.
proc means data=smallmice mean stderr;
var weight;
class day;
run;
The MEANS Procedure
Analysis Variable : weight
N
day Obs Mean Std Error
---------------------------------------------------
2 14 206.2857143 7.9569091
5 14 376.9285714 12.7414976
8 14 545.1428571 15.5852343
11 14 684.2857143 27.4036631
14 14 801.7142857 35.7411987
17 14 864.4285714 36.6791425
20 14 945.2857143 32.2497855
---------------------------------------------------
Figure 5.1, page 122.
goptions reset = all ; axis1 order =(2 to 20 by 3) label=(a=0 'Days') minor=none; axis2 order = (0 to 1200 by 200) label = (a=90 'Weight (mg)') minor=none ; symbol1 interpol=std2mjt v=none color=red r=1; proc gplot data=smallmice; plot weight*day / haxis = axis1 vaxis=axis2; run; quit;
Table 5.2, page 132.
data small; set smallmice; cont_day = day; cont_day2 = day**2; cont_day3 = day**3; run; proc mixed data = small method = reml; class id day; model weight = cont_day/ solution ddfm = bw; repeated day/ subject=id type = unstructured; run; [...output omitted...]
Solution for Fixed Effects
Standard
Effect Estimate Error DF t Value Pr > |t|
Intercept 104.76 4.3891 13 23.87 <.0001
cont_day 41.4580 1.2904 13 32.13 <.0001
proc mixed data = small method = reml;
class id day;
model weight = cont_day cont_day2/ solution ddfm = bw;
repeated day/ subject=id type = unstructured;
run;
[...output omitted...]
Solution for Fixed Effects
Standard
Effect Estimate Error DF t Value Pr > |t|
Intercept 89.5909 4.5755 13 19.58 <.0001
cont_day 64.1899 2.3275 13 27.58 <.0001
cont_day2 -1.1105 0.09463 13 -11.74 <.0001
proc mixed data = small method = reml;
class id day;
model weight = cont_day cont_day2 cont_day3/ solution ddfm = bw;
repeated day/ subject=id type = unstructured;
run;
[...output omitted...]
Solution for Fixed Effects
Standard
Effect Estimate Error DF t Value Pr > |t|
Intercept 92.3225 5.8909 13 15.67 <.0001
cont_day 60.1419 5.9710 13 10.07 <.0001
cont_day2 -0.4181 0.9452 13 -0.44 0.6655
cont_day3 -0.02369 0.03218 13 -0.74 0.4747
Table 5.3, page 132.
proc mixed data = small method = reml;
class id day;
model weight = cont_day cont_day2/ solution ddfm = bw covb;
repeated day/ subject=id type = unstructured;
run;
[...output omitted...]
Covariance Matrix for Fixed Effects
Row Effect Col1 Col2 Col3
1 Intercept 20.9351 -1.8105 0.1222
2 cont_day -1.8105 5.4173 -0.1833
3 cont_day2 0.1222 -0.1833 0.008954
Table 5.4, page 133.
Left side of table only.
proc mixed data = small method = reml;
class id day;
model weight = cont_day cont_day2/ solution ddfm = bw outpredm = smallpred;
repeated day/ subject=id type = unstructured ;
run;
proc means data =smallpred mean ;
class day;
var pred stderrpred;
run;
The MEANS Procedure
N
day Obs Variable Label Mean
-------------------------------------------------------------------
2 14 Pred Predicted Mean 213.5288267
StdErrPred Std Err Pred 5.7922990
5 14 Pred Predicted Mean 382.7788698
StdErrPred Std Err Pred 10.2051734
8 14 Pred Predicted Mean 532.0406668
StdErrPred Std Err Pred 14.2582268
11 14 Pred Predicted Mean 661.3142178
StdErrPred Std Err Pred 17.5878149
14 14 Pred Predicted Mean 770.5995228
StdErrPred Std Err Pred 20.4445870
17 14 Pred Predicted Mean 859.8965817
StdErrPred Std Err Pred 23.2891950
20 14 Pred Predicted Mean 929.2053946
StdErrPred Std Err Pred 26.7038265
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