A Step by Step Guide for SPSS and Exercise Studies

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Statistical tests 121 samples t-test. You can also use the Casewise diagnostics in Statistics (see below). To identify outliers in the values of the dependent variable create a scatterplot of its standardised residuals (use Save below to save these residuals in the data file). To detect multivariate outliers among the independent variables, that is, cases with extreme values on a combination of variables, use the Mahalanobis distance or the Leverage value (see Save below). 3. The independent variables should not be very highly correlated (r >.90) or perfectly correlated (i.e., r = 1). The first condition is called multicollinearity, the second condition is called singularity. Both conditions indicate that the independent variables contain almost identical information and, therefore, some of them should be deleted. Singularity appears when a variable is a combination (e.g., a sum or product) of other variables. To test for multicollinearity or singularity, use the Collinearity diagnostics in Statistics (see below). 4. The residuals of the regression analysis should meet the same assumptions described for ANOVA tests. See General Linear Model/Univariate in the Analyze menu for a discussion of these assumptions and how to test them. Use the Plots and Save options below to perform the residual analysis. How to carry out the test Suppose you have constructed a test to assess the performance of a group of athletes and you want to examine how well their performance can be predicted by measures of strength and flexibility (Figure 36). Insert the performance measure in the Dependent box and the strength and flexibility measures in the Independent(s) box. The independent variables can be grouped into small subsets (blocks). To add a second subset of variables click Next. To move from one subset to another click Next and Previous. These subsets are required when you want to perform a hierarchical regression analysis. With this analysis, the amount of prediction of each block of independent variables is assessed separately in a sequential order (see Change Statistics in Table 46). The grouping of the independent variables into different blocks should be based on a certain theoretical framework or on previous research findings (Dialog box 82). There are several methods for carrying out a regression analysis. You are advised to refer to appropriate statistical texts to find out which one suits your research design. Enter is a commonly used method which assesses the predictive ability of all independent variables simultaneously. Tabachnick and Fidell (1996) warn against the use of the stepwise method. You can specify different methods for different subsets of independent variables. Furthermore, you can limit the analysis to some cases (individuals). For example, you may want to analyse males only. Move gender into the Selection Variable box and click Rule (Dialog box 83). Select cases where gender=1 (assuming that this is the code you have assigned to males in the data file). Click Continue. In Dialog box 82 click Statistics to open Dialog box 84. Estimates of regression coefficients offer an indication of the predictive ability of the
122 Statistical tests Figure 36 Dialog box 82 independent variables. Model fit provides a number of statistical indices (multiple R, R squared, adjusted R squared, F value and its significance level) which are used to evaluate the results of the regression analysis. The R square change is important as it shows the change in the prediction of the dependent variable by adding another block of independent variables. The R square change
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A Step-by-Step Guide to SPSS for Sp
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First published 2001 by Routledge 1
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Contents Preface Acknowledgements x
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Contents 4 Chart and table options
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Preface This book intends to fill i
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Acknowledgements The comments and s
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2 Introduction variety of options a
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4 Introduction Data Entry Each row
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6 Introduction Dialog box 3 Dialog
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8 Data handling Dialog box 5 Dialog
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14 Data handling Dialog box 14 Tabl
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26 Data handling Merge File (Add Ca
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28 Data handling Dialog box 25 Tabl
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3 Statistical tests Analyze A varie
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50 Statistical tests Table 7 Dialog
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52 Statistical tests Dialog box 53
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60 Statistical tests Custom Tables/
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66 Statistical tests How to carry o
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5 Miscellaneous options Utilities V
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250 Suggested reading Pedhazur, E.
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252 Index discriminant analysis 2,
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A Step by Step Guide for SPSS and Exercise Studies

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