Quantitative psychological research the complete student's companion

Description

Cover Half Title Title Copyright Dedication Brief contents Detailed contents of chapters Preface Acknowledgements PART 1 INTRODUCTION CHAPTER 1 The methods used in psychological research Introduction What is the purpose of research? What is a method? Why have a method? Tensions between control and ecological validity Distinctions between quantitative and qualitative methods Is psychology a science? Ethical issues in psychological research Summary PART 2 CHOICE OF TOPIC, MEASURES AND RESEARCH DESIGN CHAPTER 2 The preliminary stages of research Introduction Choice of topic Focusing on a specific area of research Choice of method Choice of hypotheses Choice of research design Measurement in psychology The choice of measures Choice of analysis Choice of participants – the sample The procedure Pilot studies Summary CHAPTER 3 Variables and the validity of research designs Introduction Variables The validity of research designs Efficacy and effectiveness The choice of hypotheses Summary CHAPTER 4 Research designs and their internal validity Introduction Types of designs Terminology Specific examples of research designs Summary PART 3 METHODS CHAPTER 5 Asking questions I: interviews and surveys Introduction Topics for questions The formats for asking questions Choosing between the formats The settings for asking questions The pilot study Summary CHAPTER 6 Asking questions II: measuring attitudes and meaning Introduction Reliability of measures Dimensions Attitude scales Techniques to measure meaning Summary CHAPTER 7 Observation and content analysis Introduction Observation Issues shared between observation and content analysis Structured observation Content analysis Summary PART 4 DATA AND ANALYSIS CHAPTER 8 Scales of measurement Introduction Examples of measures Scales of measurement The relevance of the four scales Indicators Statisticians and scales Summary CHAPTER 9 Summarising and describing data Introduction Numerical methods Graphical methods The distribution of data Summary CHAPTER 10 Going beyond description Introduction Hypothesis testing Probability Statistical significance Error types Calculating the probability of the outcome of research One- and two-tailed tests Summary CHAPTER 11 Samples and populations Introduction Statistics Parameters Choosing a sample Confidence intervals Summary CHAPTER 12 Analysis of differences between a single sample and a population Introduction z-Tests One-group t-tests Confidence intervals for means z-Test comparing a sample proportion with a population proportion Further graphical displays Identifying outliers with standardised scores Summary CHAPTER 13 Effect size and power Introduction Limitations of statistical significance testing Effect size Statistical power Summary CHAPTER 14 Parametric and non-parametric tests Introduction Parametric tests The assumptions of parametric tests Non-parametric tests for one-group designs Summary CHAPTER 15 Analysis of differences between two levels of an independent variable Introduction Parametric tests Non-parametric tests Summary CHAPTER 16 Preliminary analysis of designs with one independent variable with more than two levels Introduction Parametric tests Non-parametric equivalents of ANOVA Summary CHAPTER 17 Analysis of designs with more than one independent variable Introduction Interactions between IVs Parametric tests Non-parametric tests Summary CHAPTER 18 Subsequent analysis after ANOVA or χ2 Introduction Contrasts Trend tests Simple effects Interpreting main effects Beyond two-way ANOVA Summary CHAPTER 19 Analysis of relationships I: correlation Introduction Correlation Non-parametric correlation Correlation and nominal data Other uses of correlation The use of correlation to evaluate reliability and validity of measures Summary CHAPTER 20 Analysis of relationships II: linear regression Introduction Simple regression Multiple regression Recommended sample size Reporting a multiple regression Mediation analysis The similarity between ANOVA and multiple regression Summary CHAPTER 21 Analysis of relationships III: logistic regression Introduction The generalised linear model Maximum likelihood estimation Simple logistic regression A single continuous predictor variable Multiple logistic regression Sequential logistic regression Assumptions Sample size Summary CHAPTER 22 Analysis of covariance (ANCOVA) Introduction An IV with two levels Assumptions of ANCOVA Reporting an ANCOVA Statistical power and ANCOVA Pre-treatment values as covariates Alternatives to ANCOVA for pre–post designs ANCOVA with more than two levels in an IV Follow-up analysis Summary CHAPTER 23 Screening data Introduction Checking for sensible values Missing data Intention to treat Outliers and influential data Distribution of data Order of checks Bootstrap Summary CHAPTER 24 Exploratory factor analysis (EFA) Introduction Types of factor analysis Finding the number of factors Initial solution Making the picture clearer Interpreting Naming the factors Checking the solution Sample size Reporting Summary CHAPTER 25 Multivariate analysis Introduction Why use multivariate techniques? Seeking a difference Controlling for covariates Exploring relationships Seeking latent variables Summary CHAPTER 26 Meta-analysis Introduction Choosing the topic of the meta-analysis Identifying the research Choosing the hypotheses to be tested Deciding which papers to obtain Extracting the necessary information Combining the results of studies Dealing with heterogeneity Reporting the results of a meta-analysis Summary CHAPTER 27 Bayesian statistics Introduction An alternative approach to probability and hypothesis testing Estimation Specifying the prior(s) Model comparison/hypothesis testing Bayes Factor Summary PART 5 SHARING THE RESULTS CHAPTER 28 Reporting research Introduction Non-sexist language A written report A verbal presentation A poster presentation Trying the presentation out Summary Appendices Appendix I: Descriptive statistics (linked to Chapter 9) Appendix II: Sampling and confidence intervals for proportions (linked to Chapter 11) Appendix III: Comparing a sample with a population (linked to Chapter 12) Appendix IV: The power of a one-group z-test (linked to Chapter 13) Appendix V: Data transformation and goodness-of-fit tests (linked to Chapter 14) Appendix VI: Seeking differences between two levels of an independent variable (linked to Chapter 15) Appendix VII: Seeking differences between more than two levels of an independent variable (linked to Chapter 16) Appendix VIII: Analysis of designs with more than one independent variable (linked to Chapter 17) Appendix IX: Subsequent analysis after ANOVA or χ2 (linked to Chapter 18) Appendix X: Correlation and reliability (linked to Chapter 19) Appendix XI: Linear regression (linked to Chapter 20) Appendix XII: Logistic regression (linked to Chapter 21) Appendix XIII: ANCOVA (linked to Chapter 22) Appendix XIV: Evaluation of measures: item and discriminative analysis, and accuracy of tests (linked to Chapter 6) Appendix XV: Exploratory factor analysis (linked to Chapter 24) Appendix XVI: Meta-analysis (linked to Chapter 26) Appendix XVII: Probability tables Appendix XVIII: Power tables Appendix XIX: Miscellaneous tables References Glossary of symbols Author index Subject index