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Understanding Regression Assumptions

Author : William D. Berry
ISBN : 080394263X
Genre : Mathematics
File Size : 37.43 MB
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Through the use of careful explanation and examples, Berry demonstrates how to consider whether the assumptions of multiple regression are actually satisfied in a particular research project. Beginning with a brief review of the regression assumptions as they are typically presented in text books, he moves on to explore in detail the substantive meaning of each assumption; for example, lack of measurement error, absence of specification error, linearity, homoscedasticity, and lack of auto-correlation.
Category: Mathematics

Data Analysis

Author : Michael Lewis-Beck
ISBN : 0803957726
Genre : Medical
File Size : 38.89 MB
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This accessible introduction to data analysis focuses on the interpretation of statistical results, in particular those which come from nonexperimental social research. It will provide social science researchers with the tools necessary to select and evaluate statistical tests appropriate for their research question. Using a consistent data-set throughout the book to illustrate the various analytic techniques, Michael Lewis-Beck covers topics such as univariate statistics, measures of association, the statistical significance of the relationship between two variables, simple regression in which the dependent variable is influenced by a single independent variable, and multiple regression.
Category: Medical

Regression Diagnostics

Author : John Fox
ISBN : 080393971X
Genre : Mathematics
File Size : 50.63 MB
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With Regression Diagnostics, researchers now have an accessible explanation of the techniques needed for exploring problems that compromise a regression analysis and for determining whether certain assumptions appear reasonable. The book covers such topics as the problem of collinearity in multiple regression, dealing with outlying and influential data, non-normality of errors, non-constant error variance and the problems and opportunities presented by discrete data. In addition, sophisticated diagnostics based on maximum-likelihood methods, scores tests, and constructed variables are introduced.
Category: Mathematics

Angewandte Statistik In Geografie Und Umweltwissenschaften

Author : Huib Ernste
ISBN : 9783728137005
Genre : Science
File Size : 39.39 MB
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Diese Einführung bietet einen Überblick über die häufigsten statistischen Methoden in den Fächern Geografie und Umweltwissenschaften. Sie bietet einen intuitiven Zugang und setzt nur wenig mathematische Kenntnisse voraus. Zugleich vermeidet sie kochbuchartige Anweisungen und vermittelt echte Einsicht in die Zusammenhänge. Mathematische Prinzipien werden erläutert und anhand von Beispielen und grafischen Darstellungen illustriert. Das Buch repräsentiert ein gewisses Spektrum unterschiedlicher Ansätze. Im Gegensatz zu anderen Einführungen bleibt es aber nicht bei der klassischen Korrelations- und Regressionsanalyse stehen, sondern führt auch zu komplexeren Methoden wie z.B. der Strukturgleichungsanalyse. Damit wird der harmonische Übergang von der einführenden Statistik in die höhere Statistik gewährleistet.
Category: Science

Applied Statistics From Bivariate Through Multivariate Techniques

Author : Rebecca M. Warner
ISBN : 9781412991346
Genre : Mathematics
File Size : 61.4 MB
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Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.
Category: Mathematics

Interpreting And Using Regression

Author : Christopher H. Achen
ISBN : 0803919158
Genre : Mathematics
File Size : 78.92 MB
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Outlines the actual procedures researchers employ, places them in the framework of statistical theory, and shows how good research takes account both of statistical theory and real world demands. Achen builds a working philosophy of regression that goes well beyond the abstract, unrealistic treatment given in previous texts. Learn more about "The Little Green Book" - QASS Series! Click Here
Category: Mathematics

Quantile Regression

Author : Lingxin Hao
ISBN : 1412926289
Genre : Mathematics
File Size : 46.94 MB
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Quantile Regression, the first book of Hao and Naiman's two-book series, establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literature exists for each subject, the authors seek to explore the natural connections between this increasingly sought-after tool and research topics in the social sciences. Quantile regression as a method does not rely on assumptions as restrictive as those for the classical linear regression; though more traditional models such as least squares linear regression are more widely utilized, Hao and Naiman show, in their application of quantile regression to empirical research, how this model yields a more complete understanding of inequality. Inequality is a perennial concern in the social sciences, and recently there has been much research in health inequality as well. Major software packages have also gradually implemented quantile regression. Quantile Regression will be of interest not only to the traditional social science market but other markets such as the health and public health related disciplines. Key Features: Establishes a natural link between quantile regression and inequality studies in the social sciences Contains clearly defined terms, simplified empirical equations, illustrative graphs, empirical tables and graphs from examples Includes computational codes using statistical software popular among social scientists Oriented to empirical research
Category: Mathematics

Regression With Dummy Variables

Author : Melissa A. Hardy
ISBN : 0803951280
Genre : Social Science
File Size : 45.96 MB
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It is often necessary for social scientists to study differences in groups, such as gender or race differences in attitudes, buying behavior, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative, dummy variables allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity, and estimating a piecewise linear regression.
Category: Social Science

Interaction Effects In Multiple Regression

Author : James Jaccard
ISBN : 0761927425
Genre : Mathematics
File Size : 22.31 MB
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Interaction Effects in Multiple Regression has provided students and researchers with a readable and practical introduction to conducting analyses of interaction effects in the context of multiple regression. The new addition will expand the coverage on the analysis of three way interactions in multiple regression analysis. Learn more about "The Little Green Book" - QASS Series! Click Here
Category: Mathematics

Handbuch Der Sozialwissenschaftlichen Datenanalyse

Author : Christof Wolf
ISBN : 9783531920382
Genre : Political Science
File Size : 73.41 MB
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Das Handbuch der sozialwissenschaftlichen Datenanalyse bietet in über 40 Kapiteln eine umfassende Darstellung multivariater Analyseverfahren. Schwerpunkte des Handbuchs bilden Grundlagen der Datenanalyse, regressionsanalytische Verfahren für Quer- und Längsschnittsdaten sowie Skalierungsverfahren. Behandelt werden u. a. OLS-, logistische und robuste Regression, Strukturgleichungsmodelle, Mehrebenen-, Panel-, Ereignisdaten- und Zeitreihenanalyse, MDS und Rasch-Modelle. Darüber hinaus werden viele neuere Verfahren dargestellt, etwa multiple Imputation, Bootstrappen, Analyse latenter Klassen und propensity score matching. Jedes Kapitel beginnt mit einer allgemein verständlichen Einführung. Es folgt eine Darstellung der mathematisch-statistischen Grundlagen. Anschließend wird jedes Verfahren anhand eines sozialwissenschaftlichen Beispiels vorgestellt. Die Beiträge enden mit Hinweisen auf typische Anwendungsfehler und einer kommentierten Literaturempfehlung.
Category: Political Science