- #How to test the homogeneity of slopes using spss version 25 how to#
- #How to test the homogeneity of slopes using spss version 25 full#
The SPSS syntax files used for executing the statistical tests can be found in the appendix.
#How to test the homogeneity of slopes using spss version 25 how to#
New to the Second Edition Three new chapters on multiple discriminant analysis, logistic regression, and canonical correlation New section on how to deal with missing data Coverage of tests of assumptions, such as linearity, outliers, normality, homogeneity of variance-covariance matrices, and multicollinearity Discussions of the calculation of Type I error and the procedure for testing statistical significance between two correlation coefficients obtained from two samples Expanded coverage of factor analysis, path analysis (test of the mediation hypothesis), and structural equation modeling Suitable for both newcomers and seasoned researchers in the social sciences, the handbook offers a clear guide to selecting the right statistical test, executing a wide range of univariate and multivariate statistical tests via the Windows and syntax methods, and interpreting the output results. This second edition now covers more topics and has been updated with the SPSS statistical package for Windows. Handbook of Univariate and Multivariate Data Analysis with IBM SPSS by Robert Ho Using the same accessible, hands-on approach as its best-selling predecessor, the Handbook of Univariate and Multivariate Data Analysis with IBM SPSS, Second Edition explains how to apply statistical tests to experimental findings, identify the assumptions underlying the tests, and interpret the findings. It is suitable for all students who need to do statistical analysis using SPSS in various departments including Psychology, Social Science, Business Studies, Nursing, Education, Health and Sport Science, Communication and Media, Geography, and Biology. Minimal prior knowledge is assumed, so the book is well designed for the novice user, but it will also be a useful reference source for those developing their own expertise in SPSS. Their understanding of SPSS users' concerns, as well as a knowledge of the type of questions students ask, form the foundation of this book.
The authors have many years of experience in teaching SPSS to students from a wide range of disciplines.
#How to test the homogeneity of slopes using spss version 25 full#
Presented in full colour and with a fresh, reader-friendly layout, this fully updated new edition also comes with a companion website featuring an array of supplementary resources for students.
The first edition of this popular book has been fully updated for IBM SPSS version 21 and also includes: chapters that explain bootstrapping and how this is used an introduction to binary logistic regression coverage of new features such as Chart Builder. A number of other helpful features are provided: regular advice boxes with tips specific to each test explanations divided into 'essential' and 'advanced' sections to suit readers at different levels frequently asked questions at the end of each chapter. It combines a step-by-step approach to each procedure with easy to follow screenshots at each stage of the process. Hinton Isabella McMurray Charlotte Brownlow SPSS Explained provides the student with all that they need to undertake statistical analysis using SPSS. Moreover, omitted terms, such as the omitted interaction if one proceeds with ANCOVA, should be reported as well.SPSS Explained by Perry R.
Therefore, this article advises to first check and report on the interaction, to use that check to decide whether a model without interaction (ANCOVA) or with interaction (MODREG) is to be preferred, and to use ANCOVA only if the criteria outlined in this article indicate a preference towards the model without interaction. If there is substantial interaction between factor and covariate, ANCOVA will result in conclusions of there being a group difference or no group difference whereas MODREG indicates that the magnitude of a group difference depends on the level of the covariate. Through a comparison of ANCOVA (which assumes non-interaction) and moderated regression (MODREG, which allows for interaction) in a worked example, this article demonstrates that omitting the check of the non-interaction assumption comes at the risk of misestimating a treatment effect or other group difference of interest. Unfortunately, many researchers report the outcomes of ANCOVA but not the outcomes of a check on that non-interaction assumption. One of the fundamental assumptions underlying ANCOVA is that of no interaction between factor and covariate. Analysis of covariance (ANCOVA) is a commonly used statistical method in experimental and quasi-experimental studies.
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