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Chapter 10
Pseudo R-square. The R
2
statistic from linear regression does not have an exact counterpart
among logistic regression models. There are, instead, multiple measures that attempt to mimic
the properties of the R
2
statistic.
Classification table. Displays the tabulated cross-classifications of the observed category by
the model-predicted category on the dependent variable.
Parameters. This group allows you to control the display of statistics related to the model
parameters.
Estimate. Displays estimates of the coefficients.
Exponentiated estimate. Displays the base of the natural logarithm raised to the power of the
estimates of the coefficients. While the estimate has nice properties for statistical testing, the
exponentiated estimate, or exp(B), is easier to interpret.
Standard error. Displays the standard error for each coefficient e stimate.
Confidence interval. Displays a confidence interval for each coefficient estimate. The
confidence level for the interval is set in the Options dialog box.
Ttest. Displays a t test of each coefficient estimate. The null hypothesis for each test is that
thevalueofthecoefficient is 0.
Covariances of parameter estimates. Displays an estimate of the covariance matrix for the
model coefficients.
Correlations of parameter estimates. Displays an estimate of the correlation matrix for the
model coefficients.
Design effect. The ratio of the variance of the estimate to the variance obtained by assuming
that the sample is a simple random sample. This is a measure of the effect of specifying a
complex design, where values further from 1 indicate greater effects.
Square root of design effect. This is a measure of the effect of specifying a complex design,
where values further from 1 indicate greater effects.
Summary statistic s for model variables. Displays summary information about the dependent
variable, covariates, and factors.
Sample desig n information. Displays summary information about the sample, including the
unweighted count and the population size.