SDA 3.5 Documentation for LOGIT


LOGIT - Logit(Logistic) and Probit Regression


logit -b batchfile


LOGIT carries out a logistic or probit regression analysis, using the method of maximum likelihood, for specified input variables. A weight variable can be used to give different weights to each case, and filter variables may be used to exclude some of the cases. If a case has missing data on ANY of the specified variables, it is excluded from all the calculations.

Recodes, dummy variables, and product terms can be generated temporarily within the program itself, so that the user will not have to create such variables before running a regression.

Ordinarily this program is invoked by the Web interface for the SDA programs, and the user does not have to deal with the keywords given in this document. Output from the program is in HTML, which can be viewed with a Web browser.

It is also possible to run the program directly by preparing a command file, which specifies the variables to be analyzed and the options to use. This document explains how to prepare such a file. The name of this batch command file is specified to the program after the ‘-b’ option flag.


The batch file contains specifications for the analysis. These specifications are given in the form "keyword = something" with one keyword per line. Keywords may be given in any order, either in upper or in lower case. The valid keywords are as follows (with significant characters shown in capital letters):

Basic Keywords

Keyword       Possible Specification          Default (if no keyword)

COefficients= PROBIT                          Calculate logit regression
                                                coefficients and results

STUdy=        path of dataset directory       Look for variables in
                                                current directory only

SAvefile=     filename to receive output      Output sent to screen
               (overwrites existing file)      (standard output)

DEP=          name of dependent variable      REQUIRED

INDep=        names of independent vars       REQUIRED
              (separated by spaces/commas)

Weight=       name of weight variable         No weighting

Filter=       name(s) and codes of filter     No filter

STRatum=      name of variable giving         No stratification for
                sample stratum                  computing standard errors
              $1: Force one stratum

CLuster=      name of variable giving         No cluster variable for
                sample cluster                  computing standard errors

GVARCase=     LOWER or UPPER                  No force to lower/upper case

DUMMYgenmax=  A number between 1 and 100      Max of 25 dummy vars can be
                (max dummy vars)                generated by the "m:" syntax
                                                for a single categorical var

NDEcimals=    number of decimals for main     3 decimal places
               results (coefficients, SE’s)

Display Options

Keyword       Possible Specification          Default (if no keyword)

COLORcoding=  Yes                             No color coding of
                                                coefficients or headings

LAnguagefile= Name of file with non-English   English labels on
                labels and messages             output

RUNtitle=     Title or comments for run       No title or comments

SHORTlist=    Yes                             Output list of all
                                                independent variables

TExt=         Yes                             No text for variables

Other Statistics

In addition to the main results, one or more of the following optional statistics can be displayed. If the product of B times the mean (BPRODuct) is requested, univariate statistics are also included automatically. The ’OTHERstats’ keyword can be repeated.

You can specify the desired number of decimal places in parentheses for univariate statistics and ’BPRODuct’ if the default, listed below, is not satisfactory. Note, however, that the number of decimals specified for ’BPRODuct’ will override the number specified for ’UNIvariate’.

Keyword       Possible Specification          Default (if no keyword)

              TTests (ndec)                   No T-tests
              EXPB                            No exp(B) for logit
              FTest (ndec)                    No Global F-test
              UNIvariate (ndec)               No univariate statistics
              BPRODuct (ndec)                 No B*Mean statistics
              COEFF (ndec)                    No covar of coefficients matrix
              CONF (90, 95, or 99)            No confidence intervals
                                               (’CONF’ alone gives 95% CI)

Technical Options

There are some other options for the maximum likelihood estimation and for ASCII output of results. These options are only available in batch mode and are not accessible from the standard SDA Web interface.

Keyword       Possible Specification          Default (if no keyword)

ASCiifile=    Name of file for ascii output   Only HTML output
               (for diagnostic purposes)

MAXIter=      Maximum number of iterations    15

NOVerbose=    Yes                             Report results of each
                                                iteration in the
                                                ASCII output file
                                                (if ’ASCiifile=’
                                                 is specified)

TOLerance=    Tolerance for convergence       .0001


The default number of decimal places for all the statistics is 3 places, except for the variance/covariance matrix of coefficients with a default of 6 decimal places. The ‘NDECimals=’ keyword is used for changing the number of decimals output for the main results (regression coefficients and their standard errors and confidence intervals).

To change the number of decimals for the other (optional) statistics, put the desired number of decimals in parentheses after specifying the statistic. Note that requesting the BPRODUCT statistics will force the output of the univariate statistics as well. And the specification of decimal places for the BPRODUCT statistics will override any specification of decimal places for the univariate statistics.


Keywords can usually be abbreviated down to the number of characters required to differentiate them from other keywords. The keyword for the name of the dependent variable, for instance, can be given as ‘dependent=’ or ‘dep=’. Either upper or lower case may be used. In the list of keywords given above, the minimum set of characters for each keyword is capitalized.


Anything on a line beginning with "#" is ignored by the batch processor and can therefore be used for comments. Blank lines are also ignored.


The form ‘keyword=yes’ may be shortened to ‘keyword’. That is, the ‘=yes’ may be omitted for those options which require no further specification. For example, ‘text=yes’ can be shortened to ‘text’.


If there is not enough room on a line to list all of the desired variables, the keyword can be repeated on a new line, and more variables can be listed. In such a case the second list is appended to the first list, for purposes of generating tables. This appending feature applies to the keywords for specifying the independent variables, the filter variables, and the ‘otherstats=’ keyword. If other keywords are repeated, the program will print an error message and stop.


# Basic logistic regression, specifying the dependent variable
# as a dummy variable
     study = /sa/testdata

     dep = spend(d:1-2)
     indep = age, educ gender

     savefile = mylogit.htm
# Run a probit regression, with t-tests and univariate statistics.
# Redefine some ranges; use weight and filter variables;
# and request descriptive text for the variables.
     dep = spend(d:1-2)
     indep = age(18-30) educ  gender

     coefficients = probit
     otherstats = ttests
     otherstats = univariate

     weight= wtvar
     filters= var21(1-3) var30(1)
     text = yes

     savefile = mylogit.htm

CSM, UC Berkeley
April 12, 2011