Title
Logistic Regression: From Introductory To Advanced Concepts And Applications
Delivery time: 8-12 business days (International)
In This Text, Author Scott Menard Provides Coverage Of Not Only The Basic Logistic Regression Model But Also Advanced Topics Found In No Other Logistic Regression Text. The Book Keeps Mathematical Notation To A Minimum, Making It Accessible To Those With More Limited Statistics Backgrounds, While Including Advanced Topics Of Interest To More Statistically Sophisticated Readers. Not Dependent On Any One Software Package, The Book Discusses Limitations To Existing Software Packages And Ways To Overcome Them.Key Features Examines The Logistic Regression Model In Detail Illustrates Concepts With Applied Examples To Help Readers Understand How Concepts Are Translated Into The Logistic Regression Model Helps Readers Make Decisions About The Criteria For Evaluating Logistic Regression Models Through Detailed Coverage Of How To Assess Overall Models And Individual Predictors For Categorical Dependent Variables Offers Unique Coverage Of Path Analysis With Logistic Regression That Shows Readers How To Examine Both Direct And Indirect Effects Using Logistic Regression Analysis Applies Logistic Regression Analysis To Longitudinal Panel Data, Helping Students Understand The Issues In Measuring Change With Dichotomous, Nominal, And Ordinal Dependent Variables Shows Readers How Multilevel Change Models With Logistic Regression Are Different From Multilevel Growth Curve Models For Continuous Interval Or Ratioscaled Dependent Variableslogistic Regression Is Intended For Courses Such As Regression And Correlation, Intermediate/Advanced Statistics, And Quantitative Methods Taught In Departments Throughout The Behavioral, Health, Mathematical, And Social Sciences, Including Applied Mathematics/Statistics, Biostatistics, Criminology/Criminal Justice, Education, Political Science, Public Health/Epidemiology, Psychology, And Sociology.
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We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Frequently Asked Questions
- Q: What topics does 'Logistic Regression: From Introductory to Advanced Concepts and Applications' cover? A: The book covers both basic and advanced logistic regression models, including unique topics like path analysis and applications to longitudinal panel data.
- Q: Who is the author of this book? A: The author is Scott Menard, who provides insights into logistic regression and its applications across various fields.
- Q: Is this book suitable for beginners in statistics? A: Yes, the book minimizes mathematical notation, making it accessible for those with limited statistics backgrounds while still addressing advanced topics.
- Q: What is the page count of this book? A: The book has a total of 392 pages.
- Q: What binding type does this book have? A: This edition is available in hardcover binding.
- Q: When was this book published? A: It was published on April 29, 2009.
- Q: Does this book include examples to illustrate concepts? A: Yes, it includes applied examples to help readers understand how concepts are implemented in logistic regression.
- Q: What type of courses is this book intended for? A: It is intended for courses such as Regression and Correlation, Intermediate/Advanced Statistics, and Quantitative Methods in various social and health sciences.
- Q: Can this book help with evaluating logistic regression models? A: Yes, it provides detailed coverage on assessing overall models and individual predictors for categorical dependent variables.
- Q: Are there any limitations discussed regarding software packages? A: Yes, the book discusses limitations of existing software packages and offers strategies to overcome them.