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st: Relative Risk Ratios


From   [email protected]
To   [email protected]
Subject   st: Relative Risk Ratios
Date   Mon, 20 Jan 2003 18:22:10 -0500

I am not sure if I have the syntax correct for running relative risk ratios. I do not have a strong background in epidemiology and am attempting to run Relative Risk Ratios (RRRs) for the first time. I have been doing some reading and the output I am getting while using Stata 7.0  to run RRRs is not making sense.  I am looking at the risk of falling (continuous outcome) given various risk factors. I have included a few examples below assessing relative risk given the presence of a particular disease diagnosis for example.  I am getting huge confidence intervals and I am having difficulty determining the "p" or the actual significance in the output.   Can anyone out there help with the syntax and the output interpretation for RRRs?
Thanks,
Beth

. mlogit m179 fallrateall, rrr

Iteration 0:   log likelihood = -460.56789
Iteration 1:   log likelihood = -460.41988
Iteration 2:   log likelihood = -460.41932
Iteration 3:   log likelihood = -460.41932

Multinomial regression                            Number of obs   =       1140
                                                 LR chi2(1)      =       0.30
                                                 Prob > chi2     =     0.5857
Log likelihood = -460.41932                       Pseudo R2       =     0.0003

------------------------------------------------------------------------------
       m179 |        RRR   Std. Err.      z    P>|z|     [95%Conf. Interval]
-------------+----------------------------------------------------------------
1            |
fallrateall |    8.05732   30.29487     0.55   0.579     .0050786    12783.19
------------------------------------------------------------------------------
(Outcome m179==0 is the comparison group)

. mlogit m180 fallrateall, rrr 

Iteration 0:   log likelihood = -357.23299
Iteration 1:   log likelihood =  -357.0605
Iteration 2:   log likelihood = -357.05925
Iteration 3:   log likelihood = -357.05925

Multinomial regression                            Number of obs   =       1140
                                                 LR chi2(1)      =       0.35
                                                 Prob > chi2     =     0.5555
Log likelihood = -357.05925                       Pseudo R2       =     0.0005

------------------------------------------------------------------------------
       m180 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
1            |
fallrateall |   .0529155   .2718481    -0.57   0.567     2.24e-06    1248.945
------------------------------------------------------------------------------
(Outcome m180==0 is the comparison group)

.  mlogit m181 fallrateall, rrr 

Iteration 0:   log likelihood = -574.59306
Iteration 1:   log likelihood = -573.42724
Iteration 2:   log likelihood = -573.40905
Iteration 3:   log likelihood = -573.40905

Multinomial regression                            Number of obs   =       1140
                                                 LR chi2(1)      =       2.37
                                                 Prob > chi2     =     0.1238
Log likelihood = -573.40905                       Pseudo R2       =     0.0021

------------------------------------------------------------------------------
       m181 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
1            |
fallrateall |   .0031174   .0122738    -1.47   0.143     1.39e-06    7.000684
------------------------------------------------------------------------------
(Outcome m181==0 is the comparison group)


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