SPSS for psychologists

Contents
Preface
	How to use this book
		Chapter 1
		Chapters 2–4
		Chapters 5–9
		Chapters 10–13
		Chapter 14
	Differences between versions of SPSS
Acknowledgements
1: Introduction
	Section 1: PSYCHOLOGICAL RESEARCH AND SPSS
		But I am studying psychology, not statistics – why do I need to learn to use SPSS?
		Asking questions and collecting data
			Levels of measurement
		Hypotheses
			Operationalisation
		Types of study design
			Correlational designs
			Experimental designs
				Quasi-experimental designs
			Related and unrelated designs in psychological research
		Populations and samples
		Parameters and statistics
		Descriptive statistics
		Confidence intervals and point estimates
		Bootstrapping
		Inferential statistics and probability
			Adjusting p values for one- and two-tailed hypotheses
		Exact and asymptotic significance
		Confidence intervals and statistical inference
		Effect size
		Statistical power
			Practical equivalence of two samples
			Statistical power and SPSS
	Section 2: GUIDE TO THE STATISTICAL TESTS COVERED
		Choosing the correct statistical procedures
	Section 3: WORKING WITH SPSS
		Data analysis using SPSS
		The different types of window used in SPSS
			The Data Editor window
			The Viewer window
			Some other windows used in SPSS
	Section 4: STARTING SPSS
		The menu and toolbars of the Data Editor window
	Section 5: HOW TO EXIT FROM SPSS
2: Data entry in SPSS
	Section 1: THE DATA EDITOR WINDOW
		What is the Data Editor window?
		The arrangement of the data in the Data Editor window
	Section 2: DEFINING A VARIABLE IN SPSS
		The Data View and Variable View
		Setting up your variables
			Variable name
			Variable type
			Variable width and decimal places
			Variable label
			Value labels
			Missing values
			Column format
			Column alignment
			Measure
			Role
			Check your settings
			Copying variable settings
	Section 3: ENTERING DATA
		A first data entry exercise
		Moving around the Data Editor window
		The value labels button
	Section 4: SAVING A DATA FILE
		To save the data to a file
	Section 5: OPENING A DATA FILE
	Section 6: DATA ENTRY EXERCISES
		Data from an unrelated (independent groups) design
		Data from a related (repeated measures) design
	Section 7: ANSWERS TO DATA ENTRY EXERCISES
		A data file for an unrelated (independent groups) design
		The data file for a related (repeated measures) design
	Section 8: CHECKING AND CLEANING DATA FILES
3: Exploring, cleaning and graphing data in SPSS
	Section 1: DESCRIPTIVE STATISTICS
	Section 2: THE DESCRIPTIVES COMMAND
		To obtain output from the Descriptives command
	Section 3: THE VIEWER WINDOW
	Section 4: THE FREQUENCIES COMMAND
		To obtain a Frequencies output
		The output produced by the Frequencies command
	Section 5: THE EXPLORE COMMAND
		Using the Explore command to analyse data from an independent groups design
		The output produced by the Explore command for an independent groups design
		Using the Explore command to analyse data from a repeated measures design
		The boxplots produced by the Explore command for a repeated measures design
	Section 6: USING DESCRIPTIVE STATISTICS TO CHECK YOUR DATA
		Checking variables in Variable View
		Using descriptive statistics to check the data
		Checking scale variables
		Finish cleaning the file
	Section 7: INTRODUCING GRAPHING IN SPSS
		Producing graphs in SPSS
		Graph types
			Boxplots
			Histogram
			Bar charts
			Error bar chart
			Line charts
			Scatterplot
	Section 8: CHART BUILDER
		To use Chart Builder
		Editing charts in the Chart Editor window
	Section 9: GRAPHBOARD TEMPLATE CHOOSER
		To use Graphboard Template Chooser
		The Graphboard Editor window
4: Data handling
	Section 1: AN INTRODUCTION TO DATA HANDLING
		An example data file
	Section 2: SORTING A FILE
		The Sort Cases command
	Section 3: SPLITTING A FILE
		Options
		Output
		Unsplitting a file
	Section 4: SELECTING CASES
		Comparing the Select Cases and Split File commands
		The Select Cases command
			Selection rules
			Selection methods
			Reselecting all cases
	Section 5: RECODING VALUES
		Recode into Different Variables
			Specifying the values to be recoded
		Recode into Same Variables
		Conditional recode
	Section 6: COMPUTING NEW VARIABLES
		Compute and Missing Values
	Section 7: COUNTING VALUES
		Conditional Count
	Section 8: RANKING CASES
		Ranking tied values
		Ranking within categories
	Section 9: DATA TRANSFORMATION
		Log transformation of decision latency data
	Section 10: DATA FILE FOR SCALES OR QUESTIONNAIRES
		A simple check on data entry
		Reversals
5: Tests of difference for  one- and two-sample designs
	Section 1: AN INTRODUCTION TO THE t-TEST
	Section 2: THE ONE-SAMPLE t-TEST
		Example study: assessing memory
		To perform a one-sample t-test
		SPSS output for one-sample t-test
			Obtained using menu items: Compare Means > One-Sample T Test
		Reporting the results
	Section 3: THE INDEPENDENT t-TEST
		Example study: the memory experiment
		To perform an independent t-test
		SPSS output for independent groups t-test
			Obtained using menu items: Compare Means > Independent-Samples T Test
		Measure of effect size
		Reporting the results
		Creating an error bar graph: independent groups design
			To obtain an error bar graph using Chart Builder
		SPSS output for bar chart
	Section 4: THE PAIRED t-TEST
		Example study: the mental imagery experiment
		To perform a paired t-test
		SPSS output for paired (or related) t-test
			Obtained using menu items: > Compare Means > Paired-Samples T Test
			Footnotes
		Measure of effect size
		R eporting the results
	Section 5: AN INTRODUCTION TO NONPARAMETRIC TESTS OF DIFFERENCE
	Section 6: THE MANN–WHITNEY TEST
		Example study: sex differences and emphasis on physical attractiveness
		How to do it
		SPSS output for Mann–Whitney U test
			Obtained using menu items: Nonparametric Tests > Legacy Dialogs > 2 Independent Samples
		Reporting the results
	Section 7: THE WILCOXON TEST
		Example study: quality of E-FIT images
		How to do it
		SPSS output for Wilcoxon matched-pairs signed-ranks test
			Obtained using menu items: Nonparametric Tests > Legacy Dialogs > 2 Related Samples
		Reporting the results
6: Tests of correlation and bivariate regression
	Section 1: AN INTRODUCTION TO TESTS OF CORRELATION
	Section 2: PRODUCING A SCATTERPLOT
		Example study: relationship between age and CFF
			How to obtain a scatterplot using Legacy Dialogs
			Producing a scatterplot with a regression line using Chart Builder
			How to add a regression equation to the scatterplot
			How to obtain a scatterplot using Graphboard Template Chooser
	Section 3: PEARSON’S r: PARAMETRIC TEST OF CORRELATION
		Example study: critical flicker frequency and age
		How to perform a Pearson’s r
		SPSS output for Pearson’s r
			Obtained using menu item: Correlate > Bivariate
		Effect sizes in correlation
		Re porting the results
	Section 4: SPEARMAN’S rS: NONPARAMETRIC TEST OF CORRELATION
		Example study: the relationships between attractiveness, believability and confidence
		How to perform Spearman’s rs
		SPSS output for Spearman’s rs
			Obtained using menu item: Correlate > Bivariate
		Reporting the results
		How to perform Kendall’s tau-b
	Section 5: PARTIAL CORRELATIONS
		How to perform a partial correlation
		SPSS output
			Obtained using: Correlate > Partial
		Reporting the results
	Section 6: COMPARING THE STRENGTH OF CORRELATION COEFFICIENTS
		Using equations
		Reporting the results
	Section 7: BRIEF INTRODUCTION TO REGRESSION
		Regression as a model
	Section 8: BIVARIATE REGRESSION
		From bivariate correlation to bivariate regression
		The bivariate regression equation
		Residuals
		Proportion of variance explained
		How to perform bivariate regression in SPSS
		SPSS output
			Obtained using: Analyze, Regression, Curve Estimation
		Using the procedure to predict Y for new cases
7: Tests for nominal data
	Section 1: NOMINAL DATA AND DICHOTOMOUS VARIABLES
		Descriptives for nominal data
		Entering nominal data into SPSS
	Section 2: CHI-SQUARE TEST VERSUS THE CHI-SQUARE DISTRIBUTION
	Section 3: THE GOODNESS OF FIT CHI-SQUARE
		To perform the goodness of fit chi-square test
	Section 4: THE MULTIDIMENSIONAL CHI-SQUARE
		General issues for chi-square
			Causal relationships
			Type of data
			The N*N contingency table
			Rationale for chi-square test
		Example study: investigating tendency towards anorexia
		To perform the multidimensional chi-square test
		SPSS output for chi-square without using Exact option
			Obtained using menu items: Descriptive Statistics > Crosstabs
			Output for first chi-square: tendency towards anorexia * employment (a variable with two levels against a variable with three levels)
		Reporting the results
			Output for second chi-square: tendency towards anorexia* education (two variables each with two levels)
		Interpreting and reporting results from chi-square
		R eporting the results
		Use of exact tests in chi-square
			Output for third chi-square: tendency towards anorexia* cultural background (a variable with two levels against a variable with three levels)
			Using the Exact option for chi-square
			Output for third chi-square (2*3) with Exact option
		Reporting the results
			Output for a 2*2 chi-square with Exact option
		Performing a chi-square using the Weight Cases option
	Section 5: THE MCNEMAR TEST FOR REPEATED MEASURES
		Example study: gender and handwriting
		How to perform the McNemar test
			McNemar test and Crosstabs command
		SPSS output for the McNemar test
			Obtained using menu items: Descriptive Statistics > Crosstabs
			How to obtain a bar chart using Chart Builder
		R eporting the results
			How to obtain a bar chart using Graphboard Template Chooser
		Note about causation and the McNemar test
8: One-way analysis of variance
	Section 1: AN INTRODUCTION TO ONE-WAY ANALYSIS OF VARIANCE (ANOVA)
		When can we use One-way ANOVA?
		How does it work?
		How do we find out if the F-ratio is significant?
		What about degrees of freedom?
		What terms are used with One-way ANOVA?
			Factors
			Levels of factors
			Between-subjects factors
			Within-subjects factors
			Main effect
		How is the F-ratio calculated?
			Between-subjects One-way ANOVA design
			Within-subjects One-way ANOVA design
			Using SPSS to calculate the F-ratio
		Effect size and ANOVA
		Planned and unplanned comparisons
	Section 2: ONE-WAY BETWEEN-SUBJECTS ANOVA, PLANNED AND UNPLANNED COMPARISONS, AND NONPARAMETRIC EQUIVALENT
		Example study: the effects of witness masking
		How to do it: using General Linear Model command
		SPSS output for One-way between-subjects ANOVA
			Obtained using menu items: General Linear Model > Univariate
		Calculating eta squared: one measure of effect size
		Reporting the results
		How to do it: using One-way ANOVA command
		SPSS output for One-way between-subjects ANOVA
			Obtained using menu items: Compare Means > One-way ANOVA
		Calculating eta squared: one measure of effect size
			Reporting the results
		Planned and unplanned comparisons
		Unplanned (post-hoc) comparisons in SPSS
			Using General Linear Model command
			Using One-way ANOVA command
		SPSS output for post-hoc tests
			Reporting the results
		Planned comparisons in SPSS
			Using One-way ANOVA command
		SPSS output for contrasts
			Obtained using menu items: Compare Means > One-way ANOVA
			R eporting the results
			Using General Linear Model command
		The Kruskal–Wallis test
		How to do it
		SPSS output for Kruskal–Wallis test
			Obtained by using menu items: Nonparametric Tests > K Independent Samples
		Reporting the results
	Section 3: ONE-WAY WITHIN-SUBJECTS ANOVA, PLANNED AND UNPLANNED COMPARISONS AND NONPARAMETRIC EQUIVALENT
		Example study: the Stroop effect
		Understanding the output
		How to do it
		SPSS output for One-way within-subjects ANOVA
			Obtained using menu items: General Linear Model > Repeated Measures
		Calculating eta squared: one measure of effect size
		Reporting the results
		Planned comparisons: more contrasts for  within-subjects factor
		Unplanned comparisons for within-subjects factor ANOVA
		The Friedman test
		How to do it
		SPSS output for Friedman test
			Obtained by using menu items: Nonparametric Tests > K Related Samples
		R eporting the results
9: Factorial analysis of variance
	Section 1: AN INTRODUCTION TO FACTORIAL ANALYSIS OF VARIANCE (ANOVA)
		Different types of Factorial ANOVA?
			Between-subjects ANOVA
			Within-subjects ANOVA
			Mixed ANOVA
		Factorial ANOVAs
		Main effects and interactions
			Interactions and moderation
			Understanding ANOVA output
	Section 2: TWO-WAY BETWEEN-SUBJECTS ANOVA
		Example study: the effect of defendant’s attractiveness and sex on sentencing
		How to do it
		SPSS output for two-way between-subjects ANOVA
			Obtained using menu items: General Linear Model > Univariate
		Calculating eta squared: one measure of effect size
		Rep orting the results
	Section 3: TWO-WAY WITHIN-SUBJECTS ANOVA
		Example study: the effects of two memory tasks on finger tapping performance
		Labelling within-subjects factors
		How to do it
			How to obtain an interaction graph
		SPSS output for two-way within-subjects ANOVA
			Obtained using menu items: General Linear Model > Repeated Measures
		Calculating eta squared: one measure of effect size
		Reporting the results
	Section 4: MIXED ANOVA
		Example study: perceptual expertise in the own-age bias
		How to do it
		SPSS output for three-way mixed ANOVA
			Obtained using menu items: General Linear Model > Repeated Measures
		Report ing the results
10: Multiple regression
	Section 1: AN INTRODUCTION TO MULTIPLE REGRESSION
		From bivariate to multiple
		An example
		How does multiple regression relate to analysis of variance?
		Causation
		When should I use multiple regression?
		The multiple regression equation
		Regression coefficients: B (unstandardised) and beta (standardised)
		R, R-squared and adjusted R-squared
		Regression methods
			Unique and shared variance
			Simultaneous or standard method
			Sequential or hierarchical method
			Statistical (or stepwise) methods
			Validating results from statistical regression methods
	Section 2: STANDARD OR SIMULTANEOUS METHOD OF MULTIPLE REGRESSION
		Example study: state anxiety
		SPSS output for standard multiple regression
			Obtained using menu items: Regression > Linear (method = enter)
		R eporting the results
	Section 3: SEQUENTIAL OR HIERARCHICAL METHOD OF MULTIPLE REGRESSION
		SPSS output for sequential multiple regression
			Obtained using menu items: Regression > Linear (method = enter; three blocks have been entered)
		A note on sequential method and regression coefficients
		Reporting the results
	Section 4: STATISTICAL METHODS OF MULTIPLE REGRESSION
		How to perform multiple regression using the stepwise method
		SPSS output for a statistical multiple regression
			Obtained using menu items: Regression > Linear (method = stepwise)
		Reporting the results
11: Analysis of covariance and multivariate analysis of variance
	Section 1: AN INTRODUCTION TO ANALYSIS OF COVARIANCE
		What does ANCOVA do?
		When should I use ANCOVA?
			An example
			Checklist for choosing one or more covariates
	Section 2: PERFORMING ANALYSIS OF COVARIANCE iN SPSS
		Example study: exposure to low levels of organophosphates
		How to check for homogeneity of regression slopes
		SPSS output from procedure to check for homogeneity of regression slopes
		How to check for linear relationship between covariate and dependent variable
		SPSS output for graph
		How to perform ANCOVA
		SPSS output for ANCOVA
		Rep orting the results
	Section 3: AN INTRODUCTION TO MULTIVARIATE ANALYSIS OF VARIANCE
		An example
		What does MANOVA do?
			Following up a significant result
		When should I use MANOVA?
			Checklist for using MANOVA
	Section 4: PERFORMING MULTIVARIATE ANALYSIS OF VARIANCE iN SPSS
		Example study: exposure to low levels of organophosphates
		How to perform MANOVA
		SPSS output for MANOVA
		Reporting the results
		A note on within-subjects designs
12: Discriminant analysis and logistic regression
	Section 1: DISCRIMINANT ANALYSIS AND LOGISTIC REGRESSION
		An example
		Similarities and differences between discriminant analysis and logistic regression
	Section 2: AN INTRODUCTION TO DISCRIMINANT ANALYSIS
		An example
		Two steps in discriminant analysis
		Assumptions
		Methods in discriminant analysis
			Choosing a method to adopt
			What does each method tell us?
			How does each method work?
	Section 3: PERFORMING DISCRIMINANT ANALYSIS iN SPSS
		Example study: reconviction among offenders
		To perform a simultaneous (enter method) discriminant analysis
		SPSS output for discriminant analysis using enter method
			Obtained using menu items: Classify > Discriminant (enter independents together)
		R eporting the results
		To perform a stepwise (or statistical) discriminant analysis
		Using discriminant function analysis to predict group membership
	Section 4: AN INTRODUCTION TO LOGISTIC REGRESSION
	Section 5: PERFORMING LOGISTIC REGRESSION ON SPSS
		Example study: reconviction among offenders
		To perform a binary logistic regression
		SPSS output for logistic regression using Enter method
			Obtained using menu items: Regression > Binary Logistic
		Reporting the results
		Using logistic regression to predict group membership
13: Factor analysis, and reliability and dimensionality of scales
	Section 1: AN INTRODUCTION TO FACTOR ANALYSIS
		How this chapter is organised
		How factor analysis relates to other statistical tests
			Correlation and covariance
			Multiple regression
			Analysis of variance
			Discriminant analysis and logistic regression
		Correlation matrix and other matrices in factor analysis
			Pearson’s r output
			Correlation matrix from factor analysis output
			Partial correlations from factor analysis output
			Reproduced correlations and residuals from factor analysis output
		When should I use factor analysis?
			Usefulness/validity of a factor analysis
		Terminology
			Component and factor
			Extraction
			Communality
			Eigenvalue
			Scree plot
			Factor loadings
			Rotation
	Section 2: PERFORMING A BASIC FACTOR ANALYSIS USING SPSS
		Hypothetical study
		How to perform the analysis
		Output from factor analysis using principal component extraction and direct oblimin rotation
			Obtained using menu items: Analyze > Dimension Reduction > Factor
		Considering the results
		Reporting the results
	Section 3: OTHER ASPECTS OF FACTOR ANALYSIS
		Other options from the Factor Analysis: Descriptives dialogue box
			Determinant
			Inverse
		Other options from the Factor Analysis: Extraction dialogue box
			Method
			Extract options
		Other options from the Factor Analysis: Rotation dialogue box
			Method
			Display
		Factor Analysis: Options dialogue box
			Coefficient Display Format
		Negative and positive factor loadings
		R factor analysis
	Section 4: RELIABILITY ANALYSIS FOR SCALES AND QUESTIONNAIRES
		Internal consistency
		How to perform a reliability analysis
		SPSS output for reliability analysis with Cronbach’s alpha
			Obtained using menu item: Scale > Reliability Analysis (model = alpha)
		Acting on the results
		SPSS output for reliability analysis with split-half
			Obtained using menu item: Scale > Reliability Analysis (model = split-half)
	Section 5: DIMENSIONALITY OF SCALES AND QUESTIONNAIRES
		To identify those items that load on a single component
		Acting on the results
		To assess the structure of items within a scale
		Acting on the results
		Important
14: Using syntax and other useful features of SPSS
	Section 1: THE SYNTAX WINDOW
		An example of a syntax command
		The Paste button and the Syntax window
			1. Duplicating actions
			2. Keeping a record of your analysis and repeating an analysis
			3. Describing the analysis you have undertaken
			4. Tweaking the parameters of a command
		The Syntax window
		Basic rules of syntax
		Saving syntax files
		Executing syntax commands
		Syntax errors
		Selecting the correct data file
	Section 2: SYNTAX EXAMPLES
		Comparing correlation coefficients
		System variables
	Section 3: GETTING HELP IN SPSS
		The Help button in dialogue boxes
		The Help menu
		What’s this?
	Section 4: OPTION SETTINGS IN SPSS
		Changing option settings
		Some useful option settings
			General tab
			Syntax Editor tab
			Viewer tab
			Data tab
			Output tab
			File Locations tab
	Section 5: PRINTING FROM SPSS
		Printing output from the Output viewer window
		Printing data and syntax files
		Special output options for pivot tables
	Section 6: INCORPORATING SPSS OUTPUT INTO OTHER DOCUMENTS
		Exporting SPSS output
	Section 7: SPSS AND EXCEL: IMPORTING AND EXPORTING DATA FILES
		Import: opening an Excel file in SPSS
		Export: saving an SPSS file to Excel
Appendix
	Data for data handling exercises: Chapter 4, Sections 1–9
	Data for data handling exercises: Chapter 4, Section 10
	Data for one-sample t-test: Chapter 5, Section 2
	Data for independent t-test: Chapter 5, Section 3
	Data for paired t-test: Chapter 5, Section 4
	Data for Mann–Whitney U test: Chapter 5, Section 6
	Data for Wilcoxon matched-pairs signed-ranks test: Chapter 5, Section 7
	Data for Pearson’s r correlation: Chapter 6, Section 3
	Data for Spearman’s rho correlation: Chapter 6, Section 4
	Data for chi-square test: Chapter 7, Section 4
	Data for McNemar test: Chapter 7, Section 5
Glossary
References
Index