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While regression analysis traces the dependence of the distribution of a response variable to see if it bears a particular (linear) relationship to one or more of the predictors, nonparametric regression analysis makes minimal assumptions about the form of relationship between the average response and the predictors. This makes nonparametric regression a more useful technique for analyzing data in which there are several predictors that may combine additively to influence the response. (An example could be something like birth order/gender/and temperament on achievement motivation). Unfortunately, researchers have not had accessible information on nonparametric regression analysisuntil now. Beginning with presentation of nonparametric regression based on dividing the data into bins and averaging the response values in each bin, Fox introduces readers to the techniques of kernel estimation, additive nonparametric regression, and the ways nonparametric regression can be employed to select transformations of the data preceding a linear least-squares fit. The book concludes with ways nonparametric regression can be generalized to logit, probit, and Poisson regression.

Mathematical statistics --- QA 278.2 .H67 2000 Regression analysis. Correlation analysis --- Regression analysis --- Nonparametric statistics --- #SBIB:303H10 --- #PBIB:2003.3 --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Distribution-free statistics --- Statistics, Distribution-free --- Statistics, Nonparametric --- Methoden en technieken: algemene handboeken en reeksen --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Nonparametric statistics. --- Regression analysis. --- Regression Analysis

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From the reviews of the First Edition."An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references."-Choice"Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent."-Contemporary Sociology"An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical."-The StatisticianIn this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.

Mathematical statistics --- QA 278.2 .H67 2000 Regression analysis. Correlation analysis --- Regression analysis --- Regression Analysis --- Méthode statistique --- Statistical methods --- Analyse de données --- Data analysis --- 519.23 --- #SBIB:303H520 --- Statistische analyse 519.23 --- Economische gedragsmodellen 519.865 --- 519.233.5 --- AA / International- internationaal --- 303.5 --- 519.536 --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Statistical analysis. Inference methods --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Correlation analysis. Regression analysis --- Theorie van correlatie en regressie. (OLS, adjusted LS, weighted LS, restricted LS, GLS, SLS, LIML, FIML, maximum likelihood). Parametric and non-parametric methods and theory (wiskundige statistiek). --- Regression analysis. --- Basic Sciences. Statistics --- Correlation and Regression Analysis --- Correlation and Regression Analysis. --- 519.233.5 Correlation analysis. Regression analysis --- 519.23 Statistical analysis. Inference methods --- Theorie van correlatie en regressie. (OLS, adjusted LS, weighted LS, restricted LS, GLS, SLS, LIML, FIML, maximum likelihood). Parametric and non-parametric methods and theory (wiskundige statistiek) --- Statistique mathematique --- Regression

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Applied Linear Statistical Models 5e is the long established leading authoritative text and reference on statistical modeling. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.

QA 278.2 Regression Analysis (Mathematical Statistics / Multivariate Analysis) - HA29 Theory and method of social science statistics (General works/ English) --- Analysis of Variance --- Linear Models --- Experimental design --- Regression analysis --- Textbooks --- Regression analysis - Textbooks --- Analysis of variance - Textbooks --- Experimental design - Textbooks --- Linear models (Statistics) - Textbooks --- Analysis of variance --- Linear models (Statistics) --- Ruimtelijke planning en ruimtelijk ontwerp --- Methoden en technieken. --- Quantitative methods in social research --- Mathematical statistics --- Statistical science --- mathematische modellen, toegepast op economie --- multivariaat --- regressie-analyse --- 519.22 --- 519.22 Statistical theory. Statistical models. Mathematical statistics in general --- Statistical theory. Statistical models. Mathematical statistics in general --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Models, Linear (Statistics) --- Mathematical models --- Statistics --- Design of experiments --- Statistical design --- Mathematical optimization --- Research --- Science --- Statistical decision --- Analysis of means --- ANOVA (Analysis of variance) --- Variance analysis --- Experiments --- Methodology --- Toegepaste statistiek. --- Modèles linéaires. --- Modèles linéaires (statistique) --- Statistique mathématique. --- Mathematical statistics. --- Experimental design.

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519.24 --- Linear models (Statistics) --- Models, Linear (Statistics) --- Mathematical models --- Mathematical statistics --- Statistics --- 519.24 Special statistical applications and models --- Special statistical applications and models --- 519.86 --- 519.86 Theory of economic-mathematical models --- Theory of economic-mathematical models --- Quantitative methods in social research --- Linear models (Statistics). --- Models --- Statistical methods --- QA 276 Mathematical statistics - Serial publications --- Linear Models --- #TELE:SISTA --- 519.535 --- Modèles linéaires (Statistique) --- Kwantitatieve sociologische onderzoeksmethoden --- Wiskundige statistiek --- Regression analysis --- Analyse de régression --- Analyse de régression --- Modele lineaire generalise --- Modele statistique --- Distribution hypergeometrique --- Statistique