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hein68
Quartz | Level 8

What statistical test would you use for this analysis?

 

Dependent variable: response rate (Y/N)

 

Independent variable: U.S. state (there is a list of 10 states)

 

Control for recruitment method: categorical variable with 2 categories

 

Thanks!

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StatDave
SAS Super FREQ

You haven't said exactly what you want to test or estimate, which is a vital thing to state when asking for a recommendation on an analysis method. Assuming that what you want to do are pairwise comparisons among the states, then this could be most easily done using PROC LOGISTIC and the LSMEANS statement. For example, these statements would provide multiple comparisons among the states adjusted for recruitment. This assumes that the effect of recruitment is the same across the states... if not than the interaction needs to be included. The ILINK option gives the estimated adjusted probability of RESPONSE="Y" for each state. The DIFF option provides a table of tests comparing the states.

proc logistic;
class state recruitment / param=glm;
model response(event="Y")=state recruitment;
lsmeans state / ilink diff;
run;

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4 REPLIES 4
PaigeMiller
Diamond | Level 26

There are probably a number of ways of handling this in SAS, but PROC LOGISTIC is where I would start.

--
Paige Miller
Reeza
Super User

General overview of Logistic regression

https://www.listendata.com/2013/04/logistic-regression-analysis-with-sas.html

 

SAS Specific example - I suggest you work through this before trying it with your data

https://documentation.sas.com/doc/en/pgmsascdc/9.4_3.4/statug/statug_logistic_examples02.htm

 


@hein68 wrote:

What statistical test would you use for this analysis?

 

Dependent variable: response rate (Y/N)

 

Independent variable: U.S. state (there is a list of 10 states)

 

Control for recruitment method: categorical variable with 2 categories

 

Thanks!


 

Ksharp
Super User
PROC CATMOD is designed for category variables anaylsis .
StatDave
SAS Super FREQ

You haven't said exactly what you want to test or estimate, which is a vital thing to state when asking for a recommendation on an analysis method. Assuming that what you want to do are pairwise comparisons among the states, then this could be most easily done using PROC LOGISTIC and the LSMEANS statement. For example, these statements would provide multiple comparisons among the states adjusted for recruitment. This assumes that the effect of recruitment is the same across the states... if not than the interaction needs to be included. The ILINK option gives the estimated adjusted probability of RESPONSE="Y" for each state. The DIFF option provides a table of tests comparing the states.

proc logistic;
class state recruitment / param=glm;
model response(event="Y")=state recruitment;
lsmeans state / ilink diff;
run;

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