I would be grateful if someone could help me with the code to find an overall p-value for heterogeneity of association by type of breast cancer bct.
Using polytomous(multinomial) logistic regression I am looking for a single p-value that test for heterogeneity across 3 groups(breast cancer type 1 (bct1)), bct2 and bct3. The variable histo is histological differences among the bc types.
Histo 1=bct1, 2=bct2 and 3=bct3. Under each bct, 1=case 0=control.
My main independent variable is agent_exp(0=unexposed and 1=exposed).
My code, log and results for finding histological differences are found below:
data ht2;
input id$ 1-7 agents_exp 8-9 histo 10-11 bct1 12-13 bct2 14-15 bct3 16-17;
datalines;
OSaa01 0 . 0 0 0
OSaa06 0 . 1 1 1
OSaa11 0 . 0 0 0
OSaa12 0 . 1 1 1
OSaa13 1 1 . 1 .
OSaa14 0 2 1 . .
OSaa15 0 1 . 1 .
OSaa19 0 . 1 1 1
OSaa21 0 . 0 0 0
OSaa22 0 . 1 1 1
OSaa23 0 . 0 0 0
OSaa24 0 1 . 1 .
OSaa29 1 . 1 1 1
OSaa30 1 2 1 . .
OSaa31 0 . 1 1 1
OSaa36 0 . 1 1 1
OSaa46 0 1 . 1 .
OSaa52 0 . 0 0 0
OSaa54 0 . 0 0 0
OSaa55 0 . 1 1 1
OSaa56 0 . . . .
OSaa58 0 . 1 1 1
OSaa63 0 2 1 . .
OSaa69 0 1 . 1 .
OSaa70 0 . 1 1 1
OSaa72 0 . 1 1 1
OSaa73 0 . 0 0 0
OSaa75 0 . 1 1 1
OSaa84 0 . 1 1 1
OSaa86 1 . 1 1 1
OSaa93 1 . 0 0 0
OSaa99 0 . 1 1 1
OSab00 0 . 1 1 1
OSab04 0 . 1 1 1
OSab12 0 . 1 1 1
OSab16 0 3 . . 1
OSab17 0 1 . 1 .
OSab19 0 . 1 1 1
OSab20 1 1 . 1 .
OSab24 0 . 1 1 1
OSab33 0 . 1 1 1
OSab37 0 . 1 1 1
OSab38 0 . 1 1 1
OSab39 0 . 1 1 1
OSab46 0 . 1 1 1
OSab50 0 . 0 0 0
OSab54 0 . 1 1 1
OSab58 0 . 0 0 0
OSab68 0 . 1 1 1
OSab70 0 . 1 1 1
OSab71 0 1 . 1 .
OSab73 0 1 . 1 .
OSab79 0 . 1 1 1
OSab84 0 . 1 1 1
OSab86 0 . 1 1 1
OSab89 0 . 1 1 1
OSab97 0 . 1 1 1
OSac02 0 . 1 1 1
OSac04 0 . 1 1 1
OSac07 1 . 0 0 0
OSac08 0 . 1 1 1
OSac13 0 . 1 1 1
OSac16 0 . 1 1 1
OSac17 1 . 1 1 1
OSac33 1 1 . 1 .
OSac34 0 . 1 1 1
OSac35 0 2 1 . .
OSac42 0 . 1 1 1
OSac43 0 . 0 0 0
OSac47 0 . 0 0 0
OSac49 0 2 1 . .
OSac52 0 . 1 1 1
OSac53 0 . 0 0 0
OSac58 0 . 1 1 1
OSac67 0 . 1 1 1
OSac74 1 1 . 1 .
OSac76 0 1 . 1 .
OSac80 0 . 0 0 0
OSac86 0 . 0 0 0
OSac87 0 . . . .
OSac88 0 . 0 0 0
OSac91 1 3 . . 1
OSac93 0 . 1 1 1
OSac97 0 . 0 0 0
OSad01 0 . 1 1 1
;
proc print data=ht2;
var id agents_exp histo bct1 bct2 bct3;
run;
proc logistic data=ht2;
class histo (ref ='2') /param=ref;
model histo = agents_exp/link=glogit;
run;
1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;
72
73 data ht2;
74 input id$ 1-7 agents_exp 8-9 histo 10-11 bct1 12-13 bct2 14-15 bct3 16-17;
75 datalines;
NOTE: The data set WORK.HT2 has 85 observations and 6 variables.
NOTE: DATA statement used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
161 ;
162
163 proc print data=ht2;
164 var id agents_exp histo bct1 bct2 bct3;
165 run;
NOTE: There were 85 observations read from the data set WORK.HT2.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.75 seconds
cpu time 0.75 seconds
166
167 proc logistic data=ht2;
168 class histo (ref ='2') /param=ref;
169 model histo = agents_exp/link=glogit;
170 run;
NOTE: PROC LOGISTIC is fitting the generalized logit model. The logits modeled contrast each response category against the
reference category (histo=2).
NOTE: Convergence criterion (GCONV=1E-8) satisfied.
NOTE: There were 85 observations read from the data set WORK.HT2.
NOTE: PROCEDURE LOGISTIC used (Total process time):
real time 0.63 seconds
cpu time 0.57 seconds
171
172
173 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;
OSaa01 |
0 |
. |
0 |
0 |
0 |
OSaa06 |
0 |
. |
1 |
1 |
1 |
OSaa11 |
0 |
. |
0 |
0 |
0 |
OSaa12 |
0 |
. |
1 |
1 |
1 |
OSaa13 |
1 |
1 |
. |
1 |
. |
OSaa14 |
0 |
2 |
1 |
. |
. |
OSaa15 |
0 |
1 |
. |
1 |
. |
OSaa19 |
0 |
. |
1 |
1 |
1 |
OSaa21 |
0 |
. |
0 |
0 |
0 |
OSaa22 |
0 |
. |
1 |
1 |
1 |
OSaa23 |
0 |
. |
0 |
0 |
0 |
OSaa24 |
0 |
1 |
. |
1 |
. |
OSaa29 |
1 |
. |
1 |
1 |
1 |
OSaa30 |
1 |
2 |
1 |
. |
. |
OSaa31 |
0 |
. |
1 |
1 |
1 |
OSaa36 |
0 |
. |
1 |
1 |
1 |
OSaa46 |
0 |
1 |
. |
1 |
. |
OSaa52 |
0 |
. |
0 |
0 |
0 |
OSaa54 |
0 |
. |
0 |
0 |
0 |
OSaa55 |
0 |
. |
1 |
1 |
1 |
OSaa56 |
0 |
. |
. |
. |
. |
OSaa58 |
0 |
. |
1 |
1 |
1 |
OSaa63 |
0 |
2 |
1 |
. |
. |
OSaa69 |
0 |
1 |
. |
1 |
. |
OSaa70 |
0 |
. |
1 |
1 |
1 |
OSaa72 |
0 |
. |
1 |
1 |
1 |
OSaa73 |
0 |
. |
0 |
0 |
0 |
OSaa75 |
0 |
. |
1 |
1 |
1 |
OSaa84 |
0 |
. |
1 |
1 |
1 |
OSaa86 |
1 |
. |
1 |
1 |
1 |
OSaa93 |
1 |
. |
0 |
0 |
0 |
OSaa99 |
0 |
. |
1 |
1 |
1 |
OSab00 |
0 |
. |
1 |
1 |
1 |
OSab04 |
0 |
. |
1 |
1 |
1 |
OSab12 |
0 |
. |
1 |
1 |
1 |
OSab16 |
0 |
3 |
. |
. |
1 |
OSab17 |
0 |
1 |
. |
1 |
. |
OSab19 |
0 |
. |
1 |
1 |
1 |
OSab20 |
1 |
1 |
. |
1 |
. |
OSab24 |
0 |
. |
1 |
1 |
1 |
OSab33 |
0 |
. |
1 |
1 |
1 |
OSab37 |
0 |
. |
1 |
1 |
1 |
OSab38 |
0 |
. |
1 |
1 |
1 |
OSab39 |
0 |
. |
1 |
1 |
1 |
OSab46 |
0 |
. |
1 |
1 |
1 |
OSab50 |
0 |
. |
0 |
0 |
0 |
OSab54 |
0 |
. |
1 |
1 |
1 |
OSab58 |
0 |
. |
0 |
0 |
0 |
OSab68 |
0 |
. |
1 |
1 |
1 |
OSab70 |
0 |
. |
1 |
1 |
1 |
OSab71 |
0 |
1 |
. |
1 |
. |
OSab73 |
0 |
1 |
. |
1 |
. |
OSab79 |
0 |
. |
1 |
1 |
1 |
OSab84 |
0 |
. |
1 |
1 |
1 |
OSab86 |
0 |
. |
1 |
1 |
1 |
OSab89 |
0 |
. |
1 |
1 |
1 |
OSab97 |
0 |
. |
1 |
1 |
1 |
OSac02 |
0 |
. |
1 |
1 |
1 |
OSac04 |
0 |
. |
1 |
1 |
1 |
OSac07 |
1 |
. |
0 |
0 |
0 |
OSac08 |
0 |
. |
1 |
1 |
1 |
OSac13 |
0 |
. |
1 |
1 |
1 |
OSac16 |
0 |
. |
1 |
1 |
1 |
OSac17 |
1 |
. |
1 |
1 |
1 |
OSac33 |
1 |
1 |
. |
1 |
. |
OSac34 |
0 |
. |
1 |
1 |
1 |
OSac35 |
0 |
2 |
1 |
. |
. |
OSac42 |
0 |
. |
1 |
1 |
1 |
OSac43 |
0 |
. |
0 |
0 |
0 |
OSac47 |
0 |
. |
0 |
0 |
0 |
OSac49 |
0 |
2 |
1 |
. |
. |
OSac52 |
0 |
. |
1 |
1 |
1 |
OSac53 |
0 |
. |
0 |
0 |
0 |
OSac58 |
0 |
. |
1 |
1 |
1 |
OSac67 |
0 |
. |
1 |
1 |
1 |
OSac74 |
1 |
1 |
. |
1 |
. |
OSac76 |
0 |
1 |
. |
1 |
. |
OSac80 |
0 |
. |
0 |
0 |
0 |
OSac86 |
0 |
. |
0 |
0 |
0 |
OSac87 |
0 |
. |
. |
. |
. |
OSac88 |
0 |
. |
0 |
0 |
0 |
OSac91 |
1 |
3 |
. |
. |
1 |
OSac93 |
0 |
. |
1 |
1 |
1 |
OSac97 |
0 |
. |
0 |
0 |
0 |
OSad01 |
0 |
. |
1 |
1 |
1 |
WORK.HT2 |
histo |
3 |
generalized logit |
Newton-Raphson |
Logits modeled use histo=2 as the reference category.
Note:66 observations were deleted due to missing values for the response or explanatory variables.
Convergence criterion (GCONV=1E-8) satisfied. |
37.384 |
40.738 |
39.273 |
44.516 |
33.384 |
32.738 |
0.6459 |
2 |
0.7240 |
0.6415 |
2 |
0.7256 |
0.6137 |
2 |
0.7358 |
1 |
0.6931 |
0.6124 |
1.2812 |
0.2577 |
1 |
-1.3863 |
1.1180 |
1.5374 |
0.2150 |
1 |
0.6931 |
1.2748 |
0.2957 |
0.5866 |
1 |
1.3863 |
1.8028 |
0.5913 |
0.4419 |
2.000 |
0.164 |
24.328 |
4.000 |
0.117 |
136.958 |
Finding a single p-value for heterogeneity is where I am stuck at:
I checked the solution on "Heterogeneity test for multinomial logistic regression' posted on 04-09-2012 but I am still stuck on my question.
Please help. Thanks.
ak.