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# RE: st: types and codes of the non-linear models

 From "BASSILI, Dr Amal STB/TDR" To "statalist@hsphsun2.harvard.edu" Subject RE: st: types and codes of the non-linear models Date Thu, 21 Feb 2013 13:59:54 +0000

```Hi Maarten,

I have done the below non-linear regression to predict incidence of a disease over years and would like to know how to interpret the trend. If b2 =0.87, does this mean that the average trend is 0.87% per year?

-----------------------------
nl exp2 : incidence_rate year
(obs = 7)

Iteration 0:  residual SS =  66.15485
Iteration 1:  residual SS =  66.15484

Source |       SS       df       MS
-------------+------------------------------         Number of obs =         7
Model |  387.559441     0           .         R-squared     =    0.8542
Residual |  66.1548444     6  11.0258074         Adj R-squared =    0.8542
-------------+------------------------------         Root MSE      =  3.320513
Total |  453.714286     6  75.6190476         Res. dev.     =  35.58776

2-parameter exp. growth curve, incidence_rate = b1*b2^year
------------------------------------------------------------------------------
incidence_~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
/b1 |   3.9e+116          .        .       .            .           .
/b2 |   .8763577   .0000164 53453.24   0.000     .8763176    .8763978
------------------------------------------------------------------------------
Parameter b1 taken as constant term in model & ANOVA table

Thanks,

Amal

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Maarten Buis
Sent: Thursday, February 21, 2013 10:36 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: types and codes of the non-linear models

On Wed, Feb 20, 2013 at 8:28 PM, BASSILI, Dr Amal     STB/TDR wrote:
> Please let me know the types and STATA codes of the non-linear models that can forecast the incidence rate of a disease if linear regression cannot be used.

The number of options open to you is just too large to list here. We could write a book-length post here with lots of options and code.
However, this would require a lot of work from us (for free), and most of it would be useless to you as it would not apply to your problem.
In order to get a more useful response you need to narrow your question down by giving us more details on what you want to do.

-- Maarten

---------------------------------
Maarten L. Buis
WZB
Reichpietschufer 50
10785 Berlin
Germany

http://www.maartenbuis.nl
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