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SYSTAT Supports
Analysis of Variance Upgrades
The Analysis of Variance feature now provides:
Bootstrap Analysis Upgrades
In previous versions, SYSTAT has analysis of the bootstrap outputs, summarizing the key parts of the outputs by histograms, computing various types of bootstrap estimates, their biases, standard errors, confidence intervals, and p-values. In SYSTAT 13, this facility is added to Hypothesis Testing and enhanced in Least-Squares Regression.
Basic Statistics Upgrades
The Basic Statistics updates in SYSTAT 13 include:
Crosstabulation Upgrades
Updates provided in the Crosstabulation (XTAB) feature include the following:
Levene’s test based on median for testing homogeneity of variances.
A SUBCAT command that categorizes the desired factors just for the purpose of the analysis.
Standard error and confidence interval for the trimmed mean.
Winsorized mean, its standard error and confidence interval.
Sample mode and mode based on kernel density estimate of data.
Interquartile range
In Hypothesis Testing, SYSTAT 13 provides bootstrap-based p-values and histograms of the test
statistic obtained from the bootstrap samples. Apart from the usual p-values of the tests, users can
now request bootstrap-based p-values in all tests for mean (one-sample z, one-sample t, two-
sample z, two-sample t, paired t, Poisson) and variance (single variance, two variances and several
In Least-Squares Linear Regression, a choice of bootstrapping residuals has been included.
Bootstrap estimates of the regression coefficients, their biases, standard errors, and confidence
intervals are then computed based on these.
Relative Risk: In a 2 x 2 table, the relative risk is the ratio of the proportions of cases having a
‘positive’ outcome in the two groups defined by row or column. Relative Risk is a common measure
of association for dichotomous variables.
Mode: SYSTAT 13 gives an option to list only the first N categories in a one-way table (frequency
distribution). This is done by adding a MODE = N option to the PLENGTH command within XTAB.
Output categorized appropriately based on the type of table, and reorganized table of measures.
Hypothesis Testing Upgrades
The Hypothesis Testing feature has been strengthened by adding tests for mean vectors of multivariate data.
One-sample Hotelling’s T2 test for mean vector of multivariate data equal to a known vector.
Two-sample Hotelling’s T2 test for equality of two mean vectors of multivariate data.
For two-sample z, two-sample t, and test for two variances, users can now directly input data in a layout where the data across the samples appear in different columns. This is in addition to the current indexed layout.
Logistic Regression
SYSTAT 13 offers more intuitive ways of analyzing binary, multinomial, conditional, and discrete choice models. Specifically:
Simplified and easy user interface and command line structure to analyze binary, multinomial,
conditional, and discrete choice models separately.
Option to specify the reference level for the binary and multinomial response models.
Simpler form of input data to analyze matched sample case-control studies with one case and
any number of controls per set.
For Discrete choice models, SYSTAT 13 provides two data layouts: ‘Choice set’ and ‘By choice’
to model an individual’s choices in response to the characteristics of the choices.
Updates in Nonparametric tests include:
Jonckeere-Terpstra test as an alternative to Mann-Whitney test: The test is used when the
treatments are ordered in terms of the response. This test is based on the sum of the k(k-1)/2 Mann-
Whitney counts (for k treatments).
Fligner-Wolfe test as an alternative to Mann-Whitney test: The test is used when one of the
treatments acts as a control, to test equality of response to control vis-à-vis all other treatments,
with a one-sided alternative. This is a Mann-Whitney test with two groups when the control is one
group and all other treatments together form another.
Post hoc (multiple comparisons) tests of Dwass-Steel-Critchlow-Fligner and of Conover-Inman
which can be used as a follow-up when a Kruskal-Wallis test shows significance.
A multiple comparison test due to Conover as a follow-up of Friedman test showing significance.