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The LOGIT command estimates the Logit Model. The method is used to model dichotomous outcome variables where the log odds of the outcome is modeled as a linear combination of the predictor variables.

In general, the format is:

LOGIT depvar indeps / options

The available options are:

beg= Specifies the BEGinning observation to be used in estimation. This option overrides the SAMPLE command and defaults to the sample range in effect.
coef= Saves the COEFficients in the variable specified. If there is an intercept it will be stored as the last coefficient.
conv= Sets the CONVergence criterion for the log-likelihood function. The value for sigma is set with CONV= and the default is 0.001.
cov= Saves the COVariance matrix of coefficients in the variable specified.
dump DUMPs the matrix of second derivatives and possibly some other output that the user normally does not want to see.
end= Specifies the ENDing observation to be used in estimation. This option overrides the SAMPLE command and defaults to the sample range in effect.
index= Saves the computed INDEX in the variable specified.
iter= Sets the maximum number of ITERations allowed. The default is 25.
list LISTs, for each observation, the value of the index I, the predicted and observed values of the dependent variable, and a plot of the predicted values. It will also print the residual statistics obtained with RSTAT. Note that the predicted values, rather than the residuals, are plotted with the LIST option in the probit and logit models since a plot of the residuals is less useful.
log Computes elasticities at the mean and weighted aggregate elasticities assuming that the explanatory variables are LOG-transformed variables.
max Prints Analysis of Variance Tables, Variance-covariance matrix, Correlation matrix, Residuals, Residual Statistics and Goodness of Fit Test for Normality. This option is equivalent to using the ANOVA, LIST, PCOV, PCOR and GF options. Users should be sure the MAX output is necessary, otherwise unnecessary calculations are required.
noconstant There will be NO CONSTANT (intercept) in the estimated equation. This option is used when the intercept is to be suppressed in the regression or when the user is supplying the intercept. This option should be used with caution as some of the usual output may be invalid. In particular, the usual R^2 is not well defined and could be negative. However, when this option is used, the raw moment R^2 may be of interest. The ANALYSIS OF VARIANCE - FROM MEAN table will not be computed if this option is used.
nonorm Used with WEIGHT= if you do not want normalized weights. Interpretation of output is sometimes difficult when weights are not normalized. Sometimes, the weights can be viewed as a sampling replication factor. Users are expected to know exactly what their weights represent.
pcor Prints the CORrelation matrix of the estimated coefficients. This should not be confused with a correlation matrix of variables which can be obtained with a STAT command.
pcov Prints the estimated asymptotic COVariance matrix of the coefficients. The matrix is the inverse of the negative of the matrix of second derivatives of the log-likelihood function.
piter= Specifies the frequency with which the ITERations will be Printed. The default is PITER=1. To prevent any information from being printed PITER=0 must be specified.
predict= Saves the PREDICTed probabilities in the variable specified.
replicate Used with WEIGHT= when the weights indicate a sample replication factor. When this option is specified the NONORM option is often desirable. The effective sample size will then be adjusted upward to be equal to the sum of the weights. The UT option is automatically in effect.
rstat Prints Residual Summary STATistics. The output includes the Durbin-Watson statistic and related residual test statistics. It also includes the Runs Test. When the LIST option is specified RSTAT is automatically turned on.
stderr= Saves the values of the STanDard ERRors of the coefficients in the variable specified.
tratio= Saves the values of the T-RATIOs in the variable specified.
weight= Specifies a variable to use as the weight for a WEIGHTed Least Squares regression. OLS with the WEIGHT= option is similar to a GLS regression with a diagonal Omega matrix. Users should also examine the NONORM, UT and REPLICATE options described above which can be used with the WEIGHT= option. More details and an example are given in the SHAZAM Reference Manual.