The CLASSIFIER keyword was added to the
PRINT subcommand. The keyword controls the display of the Classifier Evaluation
Metrics table in the output. The table shows how well a classification model fits the data compared
to a random assignment. For more information, see ROC Analysis: Display.
Performance enhancements
Memory consumption has been improved when performing transformations.
Application start time is now improved on Microsoft Windows machines.
Improved support for importing Cognos BI data into the application.
Support for the Microsoft Access database with the Office 2016 drivers.
IBM SPSS Statistics
26.0
Analyze procedures
Quantile Regression
Models the relationship between a set of predictor (independent) variables
and specific percentiles (or "quantiles") of a target (dependent) variable, most often the median.
For more information, see Quantile Regression.
Quantile regression makes no assumptions about the distribution of the
target variable, tends to resist the influence of outlying observations, and is widely used for
researching in industries such as ecology, healthcare, and financial economics.
ROC Analysis
Assesses the accuracy of model predictions by plotting sensitivity versus
(1-specificity) of a classification test (as the threshold varies over an entire range of diagnostic
test results). ROC Analysis supports the inference regarding a single AUC, precision-recall (PR)
curves, and provides options for comparing two ROC curves that are generated from either independent
groups or paired subjects. For more information, see ROC Analysis.
Bayesian Statistics
One-way Repeated Measures ANOVA
This new procedure measures one factor from the same subject at each
distinct time point or condition, and allows subjects to be crossed within the levels. It is assumed
that each subject has a single observation for each time point or condition (as such, the
subject-treatment interaction is not accounted for).
One Sample Binomial enhancements.
The procedure provides options for executing Bayesian one-sample inference
on Binomial distribution. The parameter of interest is π, which denotes the probability of success
in a fixed number of trials that may lead to either success or failure. Note that each trial is
independent of each other, and the probability π remains the same in each trial. A binomial random
variable can be seen as the sum of a fixed number of independent Bernoulli trials.
One Sample Poisson enhancements
The procedure provides options for executing Bayesian one-sample inference
on Poisson distribution. Poisson distribution, a useful model for rare events, assumes that within
small time intervals, the probability of an event to occur is proportional to the length of waiting
time. A conjugate prior within the Gamma distribution family is used when drawing Bayesian
statistical inference on Poisson distribution.
Reliability Analysis
The procedure had been updated to provide options for Fleiss' Multiple Rater
Kappa statistics that assess the interrater agreement to determine the reliability among the various
raters. A higher agreement provides more confidence in the ratings reflecting the true circumstance.
The Fleiss' Multiple Rater Kappa options are available in the Reliability Analysis: Statistics
dialog.
Command enhancements
MATRIX-END MATRIX command
Long variable names (up to 64 bytes) can be used to name a matrix or vector
name (such as COMPUTE, CALL, PRINT,
READ, WRITE, GET, SAVE,
MGET, MSAVE, DISPLAY,
RELEASE, and so on).
Variable names that are included in a vector or matrix object are truncated
to 8 bytes. This is because the matrix/vector structure is an array of numbers, and each number can
match a string only up to 8 bytes. Long names (up to 64 bytes) are supported only when explicitly
specified.
Long variable names are supported in GET and
SAVE commands when explicitly specified on the /VARIABLES
subcommand (and when specified on the /STRINGS subcommand for the
SAVE command). Variable names for GET and
SAVE commands are truncated to 8 bytes when they are referenced through a vector
in the /NAMES subcommand.
The GET, SAVE,
MGET, or MSAVE statements support both dataset references and
physical file specifications.
MATRIX-END MATRIX now supports statistical functions that
were previously only supported by the COMPUTE command (for example
IDF.CHISQ, CDF.NORMAL, NCDF.F, and so
on).
GENLINMIXED command
New Covariance Type structures ARH1 &
CSH, Random Effects. The CSH and ARH1
options were added to the /RANDOM subcommand (keyword
COVARIANCE_TYPE).
New Covariance Type structures ARH1 &
CSH, Repeated Effects. The CSH and ARH1
options were added to the /DATA_STRUCTURE subcommand (keyword
COVARIANCE_TYPE).
Kenward - Roger Degree of Freedom method. The
KENWARD_ROGER option was added to the /BUILD_OPTIONS
subcommand (keyword DF_METHOD).
Kronecker Covariance types. The options UN_AR1,
UN_CS, UN_UN were added to the
/DATA_STRUCTURE subcommand (keyword COVARIANCE_TYPE).
New KRONECKER_MEASURES keyword. The keyword is used for
specifying a list of variables for the /DATA_STRUCTURE subcommand. The keyword
should be used only when COVARIANCE_TYPE is one of three Kronecker types. The
rules for KRONECKER_MEASURES are the same as for
REPEATED_MEASURES. When both specifications are in effect, they may or may not
have common fields, but cannot be exactly the same (regardless of whether they are in the same
order).
MIXED command
DFMETHOD keyword introduced on the
CRITERIA subcommand.
KRONECKER keyword added to the
REPEATED subcommand. The keyword should be used only when
COVTYPE is one of three following Kronecker types.
UN_AR1, UN_CS, and
UN_UN options added to the COVTYPE keyword on the
REPEATED subcommand.
INSERT HIDDEN feature
You can use the INSERT HIDDEN feature in the Production
Facility command line interface to submit jobs to the SPSS® Statistics Server.
When the Production Facility command line interface is used in conjunction with the Microsoft
Windows Task Scheduler/MacOS Automator for scheduling jobs, you can effectively replace IBM® SPSS Collaboration and Deployment Services for processing SPSS Statistics jobs.