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This edited work is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource to go to for practical and sound advice from leading experts in quantitative methods.
Quantitative research. --- Social sciences --- Psychology --- Research --- Methodology.
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This publication provides a clear, step-by-step process of examining and cleaning data in order to decrease error rates and increase both the power and replicability of results.
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Jason W. Osborne's Best Practices in Logistic Regression provides students with an accessible, applied approach that communicates logistic regression in clear and concise terms. The book effectively leverages readers' basic intuitive understanding of simple and multiple regression to guide them into a sophisticated mastery of logistic regression. Osborne's applied approach offers students and instructors a clear perspective, elucidated through practical and engaging tools that encourage student comprehension.
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In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. The author returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.
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Transformations (Mathematics) --- Data transmission systems.
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