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Some New Logistic Differential Models

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Logistic Regression Using SAS

edition describes many new features of PROC LOGISTIC, including conditional logistic regression, exact logistic regression, generalized logit;

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Logistic Regression Using SAS

edition describes many new features of PROC LOGISTIC, including conditional logistic regression, exact logistic regression, generalized logit;

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Evolution of Biological Systems in Random Media

difference or differential equations in a given space X of the following type and dxt/dt = g(Xt, y), here, the vector x describes the state of the;

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Evolution of Biological Systems in Random Media

difference or differential equations in a given space X of the following type and dxt/dt = g(Xt, y), here, the vector x describes the state of the;

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A Look at the New Logistic Models with Polynomial Variable Transfer

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A Course in Item Response Theory and Modeling with Stata

logistic regression. Application-oriented discussions follow next. These cover the one-, two-, and three-parameter logistic models, polytomous item;

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Logistic Regression

In this text, author Scott Menard provides coverage of not only the basic logistic regression model but also advanced topics found in no;

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Logistic Regression Models

Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially;

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Logistic Regression Models

Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially;

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Practical Guide to Logistic Regression

Practical Guide to Logistic Regression covers the key points of the basic logistic regression model and illustrates how to use it properly;

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Practical Guide to Logistic Regression

Practical Guide to Logistic Regression covers the key points of the basic logistic regression model and illustrates how to use it properly;

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Interaction Effects in Logistic Regression

This book provides an introduction to the analysis of interaction effects in logistic regression by focusing on the interpretation of the;

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Applied Logistic Regression Analysis

The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also;

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Handbook of Differential Equations: Ordinary Differential Equations

The book contains seven survey papers about ordinary differential equations. The common feature of all papers consists in the fact that;

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Interpreting and Visualizing Regression Models Using Stata

multilevel models, models where time is a continuous predictor, models with time as a categorical predictor, nonlinear models (such as logistic or;

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Exact Solutions and Invariant Subspaces of Nonlinear Partial Differential Equations in Mechanics and Physics

for nonlinear operators and their crucial new properties. This practical reference deals with various partial differential equations (PDEs;

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Stochastic Differential Equations

stochastic applications of population growth models including logistic, generalized logistic, Gompertz, negative exponential, and linear. Ideal for;

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Neural Networks with Discontinuous/Impact Activations

This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities;

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Applied Logistic Regression

A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded;

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Applied Logistic Regression

From the reviews of the First Edition. An interesting, useful, and well-written book on logistic regression models ...Hosmer and Lemeshow;

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Analyzing Linguistic Variation - Statistical Models & Methods

The book explains the theory and practice of using logistic regression for the description of language variation, including a comprehensive;

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Dynamics of Entry and Market Evolution

This book discusses both competitive and game theory models of industry growth through new technology, innovations and new entry, and;

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Predicting Who Will Graduate

work required to build four predictive models for entering freshmen: logistic regression, automatic cluster detection, neural network, and;

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Statistical Models For Causal Analysis

, logistic regression, multinomial logistic regression and survival models. The goal is to impart a working knowledge of these models with a minimum;

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Data Analysis

of the third edition include: a new chapter on logistic regression; expanded treatment of mixed models for data with;

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Data Analysis

of the third edition include: a new chapter on logistic regression; expanded treatment of mixed models for data with;

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