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SPSS® 12.0 Command Syntax Reference

SPSS® 12.0 Command Syntax Reference

SPSS® 12.0 Command Syntax Reference

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PROBIT 1269<br />

You can request one or both of the models on the MODEL subcommand. The default is PROBIT<br />

if the subcommand is not specified or is specified with no keyword.<br />

PROBIT Probit response model. This is the default.<br />

LOGIT Logit response model.<br />

BOTH Both probit and logit response models. PROBIT displays all the output for the logit<br />

model followed by the output for the probit model.<br />

• If subgroups and multiple-predictor variables are defined, PROBIT estimates a separate<br />

intercept, , for each subgroup and a regression coefficient, , for each predictor.<br />

a j<br />

LOG Subcommand<br />

LOG specifies the base of the logarithmic transformation of the predictor variables or<br />

suppresses the default log transformation.<br />

• LOG applies to all predictors.<br />

• To transform only selected predictors, use COMPUTE commands before the Probit<br />

procedure. Then specify NONE on the LOG subcommand.<br />

• If LOG is omitted, a logarithm base of 10 is used.<br />

• If LOG is used without a specification, the natural logarithm base e (2.718) is used.<br />

• If you have a control group in your data and specify NONE on the LOG subcommand, the<br />

control group is included in the analysis. See the NATRES subcommand on p. 1270.<br />

You can specify one of the following on LOG:<br />

value Logarithm base to be applied to all predictors.<br />

NONE No transformation of the predictors.<br />

Example<br />

PROBIT R OF N BY ROOT (1,2) WITH X<br />

/LOG = 2.<br />

• LOG specifies a base-2 logarithmic transformation.<br />

CRITERIA Subcommand<br />

Use CRITERIA to specify the values of control parameters for the PROBIT algorithm. You can<br />

specify any or all of the keywords below. Defaults remain in effect for parameters that are<br />

not changed.<br />

OPTOL(n) Optimality tolerance. Alias CONVERGE. If an iteration point is a feasible<br />

point and the next step will not produce a relative change in either the parameter<br />

vector or the log-likelihood function of more than the square root of n,<br />

an optimal solution has been found. OPTOL can also be thought of as the<br />

number of significant digits in the log-likelihood function at the solution. For<br />

example, if OPTOL=10 -6 , the log-likelihood function should have approxi-<br />

b i

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