Appropriate statistical method/procedure

[timothy19]

Hi Everyone, 

I need your help to be able to use the appropriate statistical procedure for my dataset below

Here is the detail of the data.
sub_id = subjects, measurement is taken on subject at different time point.
position: where measurement is taken (anterior or posterior)
time_in_seconds: time to apply treatment
resistant:
force: force of treatment application
The y variable is whether there is a block after treatment has been applied i.e. y =1 or there is a gap y= 0 and it also contains missing data.

Question:
I want to know how Time+Force+resistance affect the outcome i.e y =gap/block

Sub_ID	Position	Time_in_Seconds	Resistance_ ohms	Force_N	y_variable
1	Ant	3.82	-23	37	1
1	Ant	4.94	-24	4.4	0
1	Ant	3.49	-41.5	15.8	1
1	Ant	3.07	-39.5	21.15	1
1	Post	3.43	-39	29	1
1	Post	3.53	-45.5	14.15	1
1	Post	4.44	-46	9.55	1
1	Post	3.37	-19	12.9	1
1	Ant	3.35	-46.5	7.2	1
1	Ant	3.19	-43	14.2	1
1	Ant	3.61	-41	24.55	1
1	Ant	4.24	-48	23.15	1
1	Post	2.09	-33	27.25	1
1	Post	2.83	-32	21.2	1
1	Post	3.26	-28	29.7	0
1	Post	3.34	-41.5	10.15	1
2	Ant	5.29	-30	10.9	1
2	Ant	4.22	-29	11.3	1
2	Ant	2.40	-15	10.2	1
2	Ant	3.32	-18.5	8.75	1
2	Post	1.85	-27	9.3	1
2	Post	4.31	-37	8.75	1
2	Post	1.82	-29.5	13.95	1
2	Post	3.98	-24.5	9.8	0
2	Ant	4.06	-39.5	21.45	1
2	Ant	2.90	-35.5	16.5	1
2	Ant	3.23	-35.5	18.2	1
2	Ant	4.24	-31	14.3	1
2	Post	2.45	-31	9.6	1
2	Post	3.51	-20	6	1
2	Post	4.27	-17.5	8.4	1
2	Post	2.67	-25.5	25	0
3	Ant	3.065092996	-40	10.7	1
3	Ant	3.74	-38	17.8	.
3	Ant	3.61	-27	10.1	0
3	Ant	2.08	-26.5	6.45	.
3	Post	2.12	-35	20.4	1
3	Post	3.244	-39	27.5	1
3	Post	4.02	-42	19.9	1
3	Post	1.94	-19	16.6	1
3	Ant	4.37	-14	4.2	0
3	Ant	4.68	-33	6.9	0
3	Ant	3.35	-30.5	8.65	1
3	Ant	1.72	-33	14.1	1
3	Post	0.81	-27	12.2	1
3	Post	3.90	-26	18.35	1
3	Post	4.19	-29	9.4	1
3	Post	4.46	-19	10.2	1
4	Ant	2.89	-42	11.3	1
4	Ant	2.20	-28	12.45	1
4	Ant	2.97	-31	19.5	1
4	Ant	2.06	-31	22.3	1
4	Post	3.35	-44.5	32.9	1
4	Post	2.10	-35	15.3	1
4	Post	3.42	-35	8.35	1
4	Post	4.16	-33	20.9	1
4	Ant	4.06	-15.5	6	1
4	Ant	5.00	-25	21.5	1
4	Ant	4.13	-33.5	24.25	1
4	Ant	5.56	-34	16.7	1
4	Post	4.14	-35	31.75	1
4	Post	4.49	-33.5	25.4	1
4	Post	4.17	-29	41.9	1
4	Post	3.85	-28	28.8	1
5	Ant	2.67	-23	28.2	0
5	Ant	1.68	-23	10.3	1
5	Ant	2.07	-19.5	9.85	1
5	Ant	1.06	-25	12.7	1
5	Post	5.02	-31	10.4	0
5	Post	2.53	-23	11.7	1
5	Post	3.40	-71.5	27.15	1
5	Post	4.78	-41.5	31.85	1
5	Ant	2.15	-42	15.95	1
5	Ant	2.89	-26.5	16.9	1
5	Ant	2.25	-33	9.8	1
5	Ant	2.76	-28	12.1	0
5	Post	3.04	-22	9	1
5	Post	4.45	-37.5	9.25	1
5	Post	4.10	-20.5	15.3	1
5	Post	4.41	-31.5	18.05	1
6	Ant	1.61	-26	18.7	1
6	Ant	1.68	-26	7.4	0
6	Ant	3.93	-29	7.4	0
6	Ant	4.45	-21.5	9.15	.
6	Post	5.48	-28	25.05	1
6	Post	4.11	-48	30.7	1
6	Post	3.20	-23	22.3	1
6	Post	2.77	-28	15.3	1
6	Ant	2.34	-22	10.95	1
6	Ant	2.25	-30	6.2	1
6	Ant	4.16	-24.5	6.6
6	Ant	4.62	-33	12	0
6	Post	2.32	-31	16.65	1
6	Post	4.03	-31	19	1
6	Post	3.43	-17	12	.
6	Post	3.51	-14	11.1	0
7	Ant	2.99	-30	7.65	1
7	Ant	1.80517419	-25	15.95	1
7	Ant	2.106053494	-32	13.8	1
7	Ant	3.096114016	-29	17.55	1
7	Post	3.167542074	-24	11.45	1
7	Post	3.338268984	-24	22.7	1
7	Post	2.659685183	-32.5	21.95	1
7	Post	3.751749917	-17	8.25	1
7	Ant	2.197529839	-25	8.8	0
7	Ant	3.664137015	-35	10.1	0
7	Ant	3.545702335	-39	9.4	0
7	Ant	2.023625001	-35	10.1	1
7	Post	2.372086883	-33	24.25	1
7	Post	3.582104056	-37.5	17.3	1
7	Post	3.45055168	-38	12.6	1
7	Post	3.841677068	-23	9.8	1
8	Ant	3.432008272	-25	18.6	0
8	Ant	2.136605495	-32.5	14.1	1
8	Ant	1.841190586	-18	7	0
8	Ant	2.15865836	-25.5	6.8	0
8	Post	3.359805409	-30	15.5	1
8	Post	3.631259765	-31	28	1
8	Post	4.674356585	-32.5	20.9	1
8	Post	4.044977037	-25	12.9	0
8	Ant	3.346860731	-28	14.6	1
8	Ant	3.850582629	-46	24.5	1
8	Ant	5.340021635	-31.5	8.5	1
8	Ant	3.980653721	-26	11.6	1
8	Post	3.704121331	-26	14.8	1
8	Post	3.848852913	-31.5	15.8	1
8	Post	4.939191479	-18	9.8	1
8	Post	3.134066196	-15	9.1	1
9	Ant	1.309024248	-25	9	1
9	Ant	3.369404446	-27	11.55	1
9	Ant	1.841284373	-26	13.15	1
9	Ant	3.675231524	-21	12.4	1
9	Post	3.06826061	-22	24.2	1
9	Post	3.59966626	-19	17.3	1
9	Post	4.466268907	-16.5	15.7	1
9	Post	1.882204503	-27	11.3	.
9	Ant	3.89896461	-25	21.1	1
9	Ant	2.295202494	-26	9	1
9	Ant	3.272687389	-24.5	4.95	0
9	Ant	4.201883396	-13	2.7	0
9	Post	4.374845784	-25	10.8	0
9	Post	4.459715564	-15.5	11.8	1
9	Post	3.227763303	-19.5	21.05	0
9	Post	2.517233031	-20.5	31.6	1

[PGStats]

This may serve as a starting point for anyone wishing to tackle this question:

data have;
infile datalines truncover;
input ID Position $ Time Resistance Force y;
datalines;
1   Ant 3.82    -23 37  1
1   Ant 4.94    -24 4.4 0
1   Ant 3.49    -41.5   15.8    1
1   Ant 3.07    -39.5   21.15   1
1   Post    3.43    -39 29  1
1   Post    3.53    -45.5   14.15   1
1   Post    4.44    -46 9.55    1
1   Post    3.37    -19 12.9    1
1   Ant 3.35    -46.5   7.2 1
1   Ant 3.19    -43 14.2    1
1   Ant 3.61    -41 24.55   1
1   Ant 4.24    -48 23.15   1
1   Post    2.09    -33 27.25   1
1   Post    2.83    -32 21.2    1
1   Post    3.26    -28 29.7    0
1   Post    3.34    -41.5   10.15   1
2   Ant 5.29    -30 10.9    1
2   Ant 4.22    -29 11.3    1
2   Ant 2.40    -15 10.2    1
2   Ant 3.32    -18.5   8.75    1
2   Post    1.85    -27 9.3 1
2   Post    4.31    -37 8.75    1
2   Post    1.82    -29.5   13.95   1
2   Post    3.98    -24.5   9.8 0
2   Ant 4.06    -39.5   21.45   1
2   Ant 2.90    -35.5   16.5    1
2   Ant 3.23    -35.5   18.2    1
2   Ant 4.24    -31 14.3    1
2   Post    2.45    -31 9.6 1
2   Post    3.51    -20 6   1
2   Post    4.27    -17.5   8.4 1
2   Post    2.67    -25.5   25  0
3   Ant 3.065092996 -40 10.7    1
3   Ant 3.74    -38 17.8    .
3   Ant 3.61    -27 10.1    0
3   Ant 2.08    -26.5   6.45    .
3   Post    2.12    -35 20.4    1
3   Post    3.244   -39 27.5    1
3   Post    4.02    -42 19.9    1
3   Post    1.94    -19 16.6    1
3   Ant 4.37    -14 4.2 0
3   Ant 4.68    -33 6.9 0
3   Ant 3.35    -30.5   8.65    1
3   Ant 1.72    -33 14.1    1
3   Post    0.81    -27 12.2    1
3   Post    3.90    -26 18.35   1
3   Post    4.19    -29 9.4 1
3   Post    4.46    -19 10.2    1
4   Ant 2.89    -42 11.3    1
4   Ant 2.20    -28 12.45   1
4   Ant 2.97    -31 19.5    1
4   Ant 2.06    -31 22.3    1
4   Post    3.35    -44.5   32.9    1
4   Post    2.10    -35 15.3    1
4   Post    3.42    -35 8.35    1
4   Post    4.16    -33 20.9    1
4   Ant 4.06    -15.5   6   1
4   Ant 5.00    -25 21.5    1
4   Ant 4.13    -33.5   24.25   1
4   Ant 5.56    -34 16.7    1
4   Post    4.14    -35 31.75   1
4   Post    4.49    -33.5   25.4    1
4   Post    4.17    -29 41.9    1
4   Post    3.85    -28 28.8    1
5   Ant 2.67    -23 28.2    0
5   Ant 1.68    -23 10.3    1
5   Ant 2.07    -19.5   9.85    1
5   Ant 1.06    -25 12.7    1
5   Post    5.02    -31 10.4    0
5   Post    2.53    -23 11.7    1
5   Post    3.40    -71.5   27.15   1
5   Post    4.78    -41.5   31.85   1
5   Ant 2.15    -42 15.95   1
5   Ant 2.89    -26.5   16.9    1
5   Ant 2.25    -33 9.8 1
5   Ant 2.76    -28 12.1    0
5   Post    3.04    -22 9   1
5   Post    4.45    -37.5   9.25    1
5   Post    4.10    -20.5   15.3    1
5   Post    4.41    -31.5   18.05   1
6   Ant 1.61    -26 18.7    1
6   Ant 1.68    -26 7.4 0
6   Ant 3.93    -29 7.4 0
6   Ant 4.45    -21.5   9.15    .
6   Post    5.48    -28 25.05   1
6   Post    4.11    -48 30.7    1
6   Post    3.20    -23 22.3    1
6   Post    2.77    -28 15.3    1
6   Ant 2.34    -22 10.95   1
6   Ant 2.25    -30 6.2 1
6   Ant 4.16    -24.5   6.6  
6   Ant 4.62    -33 12  0
6   Post    2.32    -31 16.65   1
6   Post    4.03    -31 19  1
6   Post    3.43    -17 12  .
6   Post    3.51    -14 11.1    0
7   Ant 2.99    -30 7.65    1
7   Ant 1.80517419  -25 15.95   1
7   Ant 2.106053494 -32 13.8    1
7   Ant 3.096114016 -29 17.55   1
7   Post    3.167542074 -24 11.45   1
7   Post    3.338268984 -24 22.7    1
7   Post    2.659685183 -32.5   21.95   1
7   Post    3.751749917 -17 8.25    1
7   Ant 2.197529839 -25 8.8 0
7   Ant 3.664137015 -35 10.1    0
7   Ant 3.545702335 -39 9.4 0
7   Ant 2.023625001 -35 10.1    1
7   Post    2.372086883 -33 24.25   1
7   Post    3.582104056 -37.5   17.3    1
7   Post    3.45055168  -38 12.6    1
7   Post    3.841677068 -23 9.8 1
8   Ant 3.432008272 -25 18.6    0
8   Ant 2.136605495 -32.5   14.1    1
8   Ant 1.841190586 -18 7   0
8   Ant 2.15865836  -25.5   6.8 0
8   Post    3.359805409 -30 15.5    1
8   Post    3.631259765 -31 28  1
8   Post    4.674356585 -32.5   20.9    1
8   Post    4.044977037 -25 12.9    0
8   Ant 3.346860731 -28 14.6    1
8   Ant 3.850582629 -46 24.5    1
8   Ant 5.340021635 -31.5   8.5 1
8   Ant 3.980653721 -26 11.6    1
8   Post    3.704121331 -26 14.8    1
8   Post    3.848852913 -31.5   15.8    1
8   Post    4.939191479 -18 9.8 1
8   Post    3.134066196 -15 9.1 1
9   Ant 1.309024248 -25 9   1
9   Ant 3.369404446 -27 11.55   1
9   Ant 1.841284373 -26 13.15   1
9   Ant 3.675231524 -21 12.4    1
9   Post    3.06826061  -22 24.2    1
9   Post    3.59966626  -19 17.3    1
9   Post    4.466268907 -16.5   15.7    1
9   Post    1.882204503 -27 11.3    .
9   Ant 3.89896461  -25 21.1    1
9   Ant 2.295202494 -26 9   1
9   Ant 3.272687389 -24.5   4.95    0
9   Ant 4.201883396 -13 2.7 0
9   Post    4.374845784 -25 10.8    0
9   Post    4.459715564 -15.5   11.8    1
9   Post    3.227763303 -19.5   21.05   0
9   Post    2.517233031 -20.5   31.6    1
;

proc sort data=have; by position id; run;

proc sgscatter data=have;
where resistance gt -50; /* remove outlier */
by position;
matrix force time resistance / group=y;
run;

[PaigeMiller]

I would start by performing a logistic regression. (PROC LOGISTIC)

[Ksharp]

It is repeated measured model, therefore you need Mixed Model of Logistic.

@SteveDenham  @lvm @StatDave  could give you right sas code .

But you better to post it at Stat forum.

https://communities.sas.com/t5/Statistical-Procedures/bd-p/statistical_procedures

[timothy19]

Thanks @Ksharp