Part of The SAGE Quantitative Research Kit, this text helps you make the crucial steps towards mastering multivariate analysis of social science data, introducing the fundamental linear and non-linear regression models used in quantitative research. Peter Martin covers both the theory and application of statistical models, and illustrates them with illuminating graphs, discussing:
· Linear regression, including dummy variablesand predictor transformations for curvilinear relationships
· Binary, ordinal and multinomial logistic regression models for categorical data
· Models for count data, including Poisson, negative binomial, and zero-inflated regression
· Checking model assumptions and the dangers of overfitting
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Dr Peter Martin is Lecturer in Applied Statistics at University College London. He has taught statistics to students of sociology, psychology, epidemiology, and other disciplines since 2003. One of the joys of being a statistician is that it opens doors to research collaborations with many people in diverse fields. Dr Martin has been involved in investigations in life course research, survey methodology, and the analysis of racism. In recent years his research has focused on health inequalities, psychotherapy, and the evaluation of healthcare services. He has a particular interest in topics around mental health.
In this engaging and well-illustrated volume of the SAGE Quantitative Research Kit, Peter Martin helps you make the crucial steps towards mastering multivariate analysis of social science data, introducing the fundamental linear and non-linear regression models used in quantitative research. The author covers both the theory and application of statistical models, with the help of illuminating graphs.
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