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IBM SPSS Statistics 19 Advanced Statistical Procedures Companion

Book Cover IBM SPSS Statistics 19 Advanced Statistical Procedures Companion
by Marija J. Norušis
ISBN-10: 0-321-74843-3
ISBN-13: 978-0-321-74843-0
464 pages

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A statistical procedure is not like a sausage: you want to know its contents; you want to know the types of questions it can be used to answer and the types of data for which it is appropriate. The goal of the IBM SPSS Statistics 19 Advanced Statistical Procedures Companion is to provide you with background information and examples for statistical procedures in the IBM SPSS Advanced and Regression Models modules. It aims to make it less likely that you will succumb to the siren song of melodic statistical procedure names and unleash a disastrous assault on a mutely suffering data file.

Contents at a glance:

Models for categorical dependent variables:
Multinomial regression models
Ordinal regression models (PLUM)
Logit and probit models
Hierarchical loglinear models

Models for time-to-event (survival) data:
Actuarial life tables
Kaplan-Meier estimates
Cox regression, with and without time-dependent covariates

Regression models:
Nonlinear regression
Two-stage least squares
Weighted least squares

Additional procedures:
Linear mixed models
Generalized linear mixed models
Variance-component estimation


  • Clear and straightforward explanations of the statistical procedures and IBM SPSS Statistics output
  • Detailed, integrated instructions for obtaining all the results shown
  • Several examples for most procedures
  • Datasets from various disciplines are analyzed and included on the accompanying CD
  • Book reviewed by IBM staff

Examples include:

  • Multinomial regression to predict degree of support for spending money on space exploration
  • Ordinal regression models to examine ratings of the justice system
  • Linear mixed models for testing hypotheses about achievement when students are clustered within schools
  • Multidimensional scaling for examining perceived body-part structure
  • Cox regression models for evaluating predictors of survival for patients with Hodgkin's disease

New to this edition:

Updated for version 19 of the IBM SPSS Statistics software. This edition includes a new chapter describing the Generalized Linear Mixed Models procedure.

© 2005-2011 Marija Norušis: IBM SPSS Statistics Guides Site designed by Kenny Kim Photography