New to stats- trying to write code for multiple linear regression using sex and age as predictors

[kplbug8]

Hello, this question may be relatively simple, I am just starting to learn all this so thank you in advance.

To simplify my data, let's say I have 1 outcome in 37 subjects. Those subjects were technically allocated to two age groups (young adult and senior), but I also want to analyse the results continuously instead of grouped by age. They were also of both sexes so I want to see if that also has an effect on the outcome. My data, for example, can look something like this (I have changed the outcome values for testing purposes):

Data;
input Sex$ Age Value;
cards;
M	13	1
M	3	0.5
F	2	0.6
M	3	0.5
M	3	0.5
M	3	0.5
F	1	0.6
F	11	1.2
F	2	0.6
M	3	0.5
M	13	1
F	2	0.6
F	3	0.6
F	3	0.6
M	9	1
M	1	0.5
M	9	1
M	9	1
F	13	1.2
M	11	1
F	11	1.2
M	11	1
M	3	0.5
F	3	0.6
M	3	0.5
M	1	0.5
M	16	1
M	11	1
M	3	0.5
M	1	0.5
M	2	0.5
F	9	1.2
F	9	1.2
M	3	0.5
F	2	0.6
F	12	1.2
F	9	1.2

I have other predictors I'd like to look into as well such as weight, date sample was collected, and so on, but am not sure if I can just add them here?

How would I go about testing to see if age and sex have an impact on the Value? So far I have tried this (inserted below), but it does not like the sex variable. Also, could I include other predictors into this same code without having to run another one?

/*Test Data*/
Data;
input Sex$ Age Value;
cards;
M	13	1
M	3	0.5
F	2	0.6
M	3	0.5
M	3	0.5
M	3	0.5
F	1	0.6
F	11	1.2
F	2	0.6
M	3	0.5
M	13	1
F	2	0.6
F	3	0.6
F	3	0.6
M	9	1
M	1	0.5
M	9	1
M	9	1
F	13	1.2
M	11	1
F	11	1.2
M	11	1
M	3	0.5
F	3	0.6
M	3	0.5
M	1	0.5
M	16	1
M	11	1
M	3	0.5
M	1	0.5
M	2	0.5
F	9	1.2
F	9	1.2
M	3	0.5
F	2	0.6
F	12	1.2
F	9	1.2


;
run;
proc reg;
model Value= Age Sex;
run;
proc reg;
model Value= Age;
run;
proc reg;
model Value= Sex;
run;
Proc reg;
model Value= Age Sex / selection= stepwise slentry=0.05;
run;
proc corr;
var Sex Age Value;
run;

I have taken one stats course so far and this was not included, so I am a bit out of my wheelhouse on this!

Thank you so much in advance,

[Reeza]

Sex is a categorical predictor and REG does not handle character variables. You will need to either manually dummy code that variable or use a different proc (recommended). In that case I would recommend PROC GLM.

I would highly, highly recommend giving your data set names. Makes it much easier to trace your code as it gets longer.

proc glm data=responses;
class sex;
model value =  age sex;
run;

proc glm data=responses;
model value= age;
run;

proc glm data=responses;
class sex;
model value = sex;
run;

proc corr data=responses;
var age value;
run;

proc sort data=responses;
by sex;
run;

proc corr data=responses;
by sex;
var age value;
run;

Note the SAS Stats training course is free.

Spoiler

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@kplbug8 wrote:

Hello, this question may be relatively simple, I am just starting to learn all this so thank you in advance.

To simplify my data, let's say I have 1 outcome in 37 subjects. Those subjects were technically allocated to two age groups (young adult and senior), but I also want to analyse the results continuously instead of grouped by age. They were also of both sexes so I want to see if that also has an effect on the outcome. My data, for example, can look something like this (I have changed the outcome values for testing purposes):

Data;
input Sex$ Age Value;
cards;
M	13	1
M	3	0.5
F	2	0.6
M	3	0.5
M	3	0.5
M	3	0.5
F	1	0.6
F	11	1.2
F	2	0.6
M	3	0.5
M	13	1
F	2	0.6
F	3	0.6
F	3	0.6
M	9	1
M	1	0.5
M	9	1
M	9	1
F	13	1.2
M	11	1
F	11	1.2
M	11	1
M	3	0.5
F	3	0.6
M	3	0.5
M	1	0.5
M	16	1
M	11	1
M	3	0.5
M	1	0.5
M	2	0.5
F	9	1.2
F	9	1.2
M	3	0.5
F	2	0.6
F	12	1.2
F	9	1.2

I have other predictors I'd like to look into as well such as weight, date sample was collected, and so on, but am not sure if I can just add them here?

How would I go about testing to see if age and sex have an impact on the Value? So far I have tried this (inserted below), but it does not like the sex variable. Also, could I include other predictors into this same code without having to run another one?

/*Test Data*/
Data;
input Sex$ Age Value;
cards;
M	13	1
M	3	0.5
F	2	0.6
M	3	0.5
M	3	0.5
M	3	0.5
F	1	0.6
F	11	1.2
F	2	0.6
M	3	0.5
M	13	1
F	2	0.6
F	3	0.6
F	3	0.6
M	9	1
M	1	0.5
M	9	1
M	9	1
F	13	1.2
M	11	1
F	11	1.2
M	11	1
M	3	0.5
F	3	0.6
M	3	0.5
M	1	0.5
M	16	1
M	11	1
M	3	0.5
M	1	0.5
M	2	0.5
F	9	1.2
F	9	1.2
M	3	0.5
F	2	0.6
F	12	1.2
F	9	1.2


;
run;
proc reg;
model Value= Age Sex;
run;
proc reg;
model Value= Age;
run;
proc reg;
model Value= Sex;
run;
Proc reg;
model Value= Age Sex / selection= stepwise slentry=0.05;
run;
proc corr;
var Sex Age Value;
run;

I have taken one stats course so far and this was not included, so I am a bit out of my wheelhouse on this!

Thank you so much in advance,

---