### sas >> Ramdom Effects Predictors for Cox Regression Model

Is is possible to incorporate random effect into a Cox Regression model
using SAS? I am thinking of a multicenter trial where time-to-event is
an outcome. Using sites as fixed effects is an option; however, the
differences between sites are really random, not fixed and should be
modeled accordingly.

Is there a provision for such analysis in SAS and, if not, can someone
explain why?

How does parametric vs. non-parametric distinction apply in this case,
if it does?

```I'm analyzing survival with Cox regression as a function of a single
predictor: experimental group membership.  This is all toward the end
of making a figure of hazard ratio coefficients as commonly seen in
medical literature, like so:

subgroup   (favors intervention)         1  (favors usual treatment)
------------------------------------------------------------
Systolic HF	<-----------o------>
Diastolic HF	<----------------o--------------->
etc...

To get the coefficients and confidence intervals for each subgroup, I
ran the Cox model limiting the sample to patients in one subgroup,
then repeated for the other. The coefficient estimates for the effect
of the intervention from the subgroup analysis were identical to the
coefficients obtained from an interaction model run on all the cases.
When the analysis was run separately by subgroup, I observed that
experimental group membership had a statistically significant effect
for systolic heart failure (HF) patients, but not for diastolic HF
patients.

I made the figure, then went back to the data to check the interaction
coefficients so I could put a p-value on each pair (systolic vs
diastolic, men vs women, young vs old, etc).  I ran the analysis on
the entire dataset using a multiplicative interaction model using
three RHS variables:

1. experimental (0/1 dummy for group membership)
2. systolic (0/1 dummy indicating type of heart failure)
3. experimental*systolic (multiplicative interaction of the 2)

I was surprised in doing this that the interaction for
experimental*systolic was only of marginal significance (p=0.07 in
stata, 0.09 in SAS).  I had expected that if one subgroup had a
statistically significant effect of experimental group membership and
the other subgroup didn't, then the interaction of experimental group
membership by subgroup should be significant.

Can anyone straighten out my logic here?  Is the problem as simple as
the fact that the interaction effect is too small to be statistically
significant, or am I committing a larger logical or statistical error
here? I have checked the construction of all the dummy and interaction
variables and they carry the right counts.

Thanks,

```

```Hi all

I need to run fixed effect for 2sls regresssions. Could you please advise me
how to do it in SAS?

Thanks  a lot

Best regards

Thu Phuong
```

```Hi I'm trying to understand how to interpret the results of a logistic
regression when there are one or more Ordinal Independent variables. eg.

y= b0+ b1x1 + b2x2+ b3x3  where y =1 or 0, x2= 1 or 2 or 3, x3=1 or 2 or 3
or 4

Can anyone also tell me how this basic sas code needs to be changed?I am
modeling y=0

rsubmit;
Proc logistic data= test;
model y = x1 x2 x3;
run;
```

```Hi everyone,
I have a simple problem that I am stuck on. I have a list of 27
predictor variables (let's assume they're all numeric for now) and I
want to run 27 logistic regression models without having to call the
macro I wrote (below) 27 times manually....I want to automate this for
efficiency purposes. At this point, I am only interested in univariate
analysis and will then move towards multivariate analysis. How can I
do this?

My macro so far:

%let list=a b c d e f g;

%macro lr (data=,riskfactor=, outcome=, outformat=);
proc logistic descending data=&data;
format &outcome &outformat;
run;
%mend;

%lr (data=anne2, riskfactor=site, outcome=mutation,
outformat=mutationnew.)

I'd like to loop through &list, using a do loop one by one, but i'm
not sure exactly how to write this. Something like:

%do i=1 %to dim(&list);

should work, but i'm not totally sure, can anyone help me with the
last couple of steps?

TIA.

NM.

```