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Contributor
Posts: 61

# matched data analysis

Hi,

I have a matched data set (shown below). I want to carry out the following analysis:

1. Descriptive table

2. conditional logistic regression unadjusted (outcome is fev)

3. conditional logistic regression adjusted (outcome is fev)

4. conditional logistic regression with interaction terms (opwo*race) (outcome is fev). Please guide me.

Thanks

 Group Type Control Id id age edu race parity wt ht opwo fev 1 Case . 5 32 9 1 0 90 5.2 1 1 1 Control 1 70 32 9 1 0 90 5.2 1 0 1 Control 2 99 35 10 1 0 90 5.2 0 0 2 Case . 12 35 12 1 2 110 5 0 1 2 Control 1 43 35 12 1 1 110 5 0 0 2 Control 2 101 33 11 1 2 110 5 0 0 3 Case . 22 25 14 3 0 110 5.4 0 1 3 Control 1 125 25 13 3 0 110 5.4 0 0 3 Control 2 51 28 12 3 0 110 5.4 0 0 4 Case . 29 27 12 2 1 95 5 1 1 4 Control 1 32 29 12 2 2 125 6.2 1 0 4 Control 2 31 27 10 2 1 95 5.5 0 0 5 Case . 40 28 10 3 2 130 6 1 1 5 Control 1 58 28 10 3 2 130 6 0 0 5 Control 2 93 27 11 3 2 130 6 1 0

Accepted Solutions
Solution
‎05-13-2016 09:27 AM
Super User
Posts: 10,770

## Re: matched data analysis

You can find some examples relate to conditional logistic in documentation.

Something like :

Example 72.11: Conditional Logistic Regression for Matched Pairs Data

``````

data have;
infile cards expandtabs truncover;
input  Group	Type \$	ControlId	id	age	edu	race	parity	wt	ht	opwo	fev;
cards;
1	Case	.	5	32	9	1	0	90	5.2 1 1
1	Control	1	70	32	9	1	0	90	5.2 1 0
1	Control	2	99	35	10	1	0	90	5.2 0 0
2	Case	.	12	35	12	1	2	110	5   0 1
2	Control	1	43	35	12	1	1	110	5   0 0
2	Control	2	101	33	11	1	2	110	5   0 0
3	Case	.	22	25	14	3	0	110	5.4 0 1
3	Control	1	125	25	13	3	0	110	5.4 0 0
3	Control	2	51	28	12	3	0	110	5.4 0 0
4	Case	.	29	27	12	2	1	95	5   1 1
4	Control	1	32	29	12	2	2	125	6.2 1 0
4	Control	2	31	27	10	2	1	95	5.5 0 0
5	Case	.	40	28	10	3	2	130	6  1 1
5	Control	1	58	28	10	3	2	130	6  0 0
5	Control	2	93	27	11	3	2	130	6  1 0
;
run;
proc logistic data=have ;
strata group;
model fev(event='1')= age edu race parity;
run;``````

All Replies
Super User
Posts: 13,523

## Re: matched data analysis

What should the descriptive "table" contain? Counts, percents, Means, standard deviations, max, min or other statistics of single variables? Combinations of variables? within groups? Correlations?

Contributor
Posts: 61

## Re: matched data analysis

Thanks; I want to have counts with percents and mean with standard deviations and range.

Super User
Posts: 10,770

## Re: matched data analysis

Can you explain

2. conditional logistic regression unadjusted (outcome is fev)

3. conditional logistic regression adjusted (outcome is fev)

Did you check the example in documentation ,there are many examples about conditional logistic regression.

What is your STRATA(conditional) variable ? GROUP ?

About interaction terms  opwo*race , Couldn't you write as

model ....=....  opwo*race ;

strata group;

or check EFFECT statement.

Contributor
Posts: 61

## Re: matched data analysis

Sure.

Unadjusted means univatiate analysis (one variable assessed for the outcome, here fev)

Adjusted means multipvariate, when more than one independent variables are added to the model simultaneously where these variables adjust the effect/association of each other on the response variable.

My matching variables are: age, edu, race and parity. I think, not sure, these can be taken as 'strata'.

Thanks

Solution
‎05-13-2016 09:27 AM
Super User
Posts: 10,770

## Re: matched data analysis

You can find some examples relate to conditional logistic in documentation.

Something like :

Example 72.11: Conditional Logistic Regression for Matched Pairs Data

``````

data have;
infile cards expandtabs truncover;
input  Group	Type \$	ControlId	id	age	edu	race	parity	wt	ht	opwo	fev;
cards;
1	Case	.	5	32	9	1	0	90	5.2 1 1
1	Control	1	70	32	9	1	0	90	5.2 1 0
1	Control	2	99	35	10	1	0	90	5.2 0 0
2	Case	.	12	35	12	1	2	110	5   0 1
2	Control	1	43	35	12	1	1	110	5   0 0
2	Control	2	101	33	11	1	2	110	5   0 0
3	Case	.	22	25	14	3	0	110	5.4 0 1
3	Control	1	125	25	13	3	0	110	5.4 0 0
3	Control	2	51	28	12	3	0	110	5.4 0 0
4	Case	.	29	27	12	2	1	95	5   1 1
4	Control	1	32	29	12	2	2	125	6.2 1 0
4	Control	2	31	27	10	2	1	95	5.5 0 0
5	Case	.	40	28	10	3	2	130	6  1 1
5	Control	1	58	28	10	3	2	130	6  0 0
5	Control	2	93	27	11	3	2	130	6  1 0
;
run;
proc logistic data=have ;
strata group;
model fev(event='1')= age edu race parity;
run;``````
Contributor
Posts: 61

## Re: matched data analysis

Thanks, it did work; will explore further. However, I can't take age edu race and parity in the model as they are matching variable and their effect has already been fixed.

Contributor
Posts: 61

## Re: matched data analysis

Hi Ksharp,

What code should I use for count (with percents) for parity, race, opwo and for mean (with std deviation) for wt ht acros fev (1 and 0)?

Thanks.

Super User
Posts: 10,770

## Re: matched data analysis

Sorry. I don't know what you are talking about. Maybe you should start a new session to discuss this .
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