Description
Springer SPSS for Starters Part 2 1st Editon 2012 Softbound by Ton J. Cleophas, Aeilko H. Zwinderman
The first part of this title contained all statistical tests that are relevant for starters on SPSS, and included standard parametric and non-parametric tests for continuous and binary variables, regression methods, trend tests, and reliability and validity assessments of diagnostic tests. The current part 2 of this title reviews multistep methods, multivariate models, assessments of missing data, performance of diagnostic tests, meta-regression, Poisson regression, confounding and interaction, and survival analyses using log tests and segmented time-dependent Cox regression. Methods for assessing non linear models, data seasonality, distribution free methods, including Monte Carlo methods and artificial intelligence, and robust tests are also covered. Each method of testing is explained using a data example from clinical practice,including every step in SPSS, and a text with interpretations of the results and hints convenient for data reporting. In order to facilitate the use of this cookbook the data files of the examples is made available by the editor through extras.springer.com. Both part 1 and 2 of this title contain a minima amount of text and maximal technical details, but we believe that this property will not refrain students from mastering the SPSS software systematics, and that, instead, it will be a help to that aim. Yet, we recommend that it will used together with the textbook 'Statistics Applied to Clinical Trials' (5th edition, Springer, Dordrecht 2012) and the e-books 'Statistics on a Pocket Calculator Part 1 and 2 (Springer, Dordrecht, 2011 and 2012) from the same authors. Preface.-1 Introduction.-2 Multistage regression.-3 Multivariate analysis using path statistics.-4 Multivariate analysis of variance.-5 Categorical data.-6 Multinomial logistic regression.-7 Missing data imputation.-8 Comparing the performance of diagnostic tests.-9 Meta-regression.-10 Poisson regression.-11 Confounding.-12 Interaction, random effect analysis of variance.-13 Log rank tests.14 Segmented Cox regression.-15 Curvilinear analysis.-16 Loess and spline modelling.-17 Assessing seasonality.-18 Monte Carlo analysis.-19 Artificial intelligence.-20 Robust tests. Final remarks. Index.