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Poisson regression

Stata's poisson command fits maximum-likelihood models of the number of occurrences (counts) of an event. In a Poisson regression model, the incidence rate for the jth observation is assumed to be given by
   r_j = exp(b_0 + b_1*x_(1,j) + ... + b_k*x_(k,j)
If E_j is the exposure, the expected number of events C_j will be
   C_j = E_j * r_j
       = exp[ ln(E_j) + b_0 + b_1*x_(1,j) + ... + b_k*x_(k,j) ]
This is the model fitted by poisson. E_j may be specified or, if not specified, is assumed to be 1.
    . poisson deaths smokes a2-a5, exposure(pyears) irr

    Iteration 0:   log likelihood = -33.823284  
    Iteration 1:   log likelihood = -33.600471  
    Iteration 2:   log likelihood = -33.600153  
    Iteration 3:   log likelihood = -33.600153  
    
    Poisson regression                                Number of obs   =         10
	                                              LR chi2(5)      =     922.93
	                                              Prob > chi2     =     0.0000
    Log likelihood = -33.600153                       Pseudo R2       =     0.9321
	
    ------------------------------------------------------------------------------
	  deaths |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
	  smokes |   1.425519   .1530638     3.30   0.001     1.154984    1.759421
	      a2 |   4.410584   .8605197     7.61   0.000     3.009011    6.464997
	      a3 |    13.8392   2.542638    14.30   0.000     9.654328    19.83809
	      a4 |   28.51678   5.269878    18.13   0.000     19.85177    40.96395
	      a5 |   40.45121   7.775511    19.25   0.000     27.75326    58.95885
	  pyears | (exposure)
    ------------------------------------------------------------------------------
The syntax of all estimation commands is the same: the name of the dependent variable is followed by the names of the independent variables, which are followed by a comma and any options. In this case, we controlled for the exposure (person-years recorded in the variable pyears) and asked that results be displayed as incidence-rate ratios rather than as coefficients.

Stata can perform stepwise Poisson regression, too. Also, Stata provides Cox regression, exponential, Weibull, and other parametric survival models, as well as logistic regression and stepwise variants of these procedures.

See New in Stata 10 for more about what was added in Stata Release 10.

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