Correlations, in general, and the Pearson product-moment correlation in particular, can be used for many research purposes, ranging from describing a relationship between two variables as a descriptive statistic to examining a relationship between two variables in a population as an inferential statistic, or to gauge the strength of an effect, or to conduct a meta-analytic study. How can correlation be more effectively used so that one doesn't misinterpret the data? This book reveals how to do this by examining Pearson r from its conceptual meaning, to assumptions, special cases of the...
Correlations, in general, and the Pearson product-moment correlation in particular, can be used for many research purposes, ranging from describing a ...
This book discusses the estimation, simulation, and interpretation of models with multiple outcomes, when these outcomes are either ordered or unordered, against the backdrop of examples relating to socioeconomic inequality. The book includes exposition of the important distinction between odds-ratios and risk-ratios, logit versus probit (and, vice-versa) as well as a step-by-step explanation of the practical computing procedures that underpin the analysis.
This book discusses the estimation, simulation, and interpretation of models with multiple outcomes, when these outcomes are either ordered or unor...
Spline Regression Models shows the nuts-and-bolts of using dummy variables to formulate and estimate various spline regression models. For some researchers this will involve situations where the number and location of the spline knots are known in advance, while others will need to determine the number and location of spline knots as part of the estimation process. Through the use of a number of straightforward examples, the authors will show readers how to work with both types of spline knot situations as well as offering practical, down-to-earth information on estimating splines.
Spline Regression Models shows the nuts-and-bolts of using dummy variables to formulate and estimate various spline regression models. For some res...
Smithson first introduces the basis of the confidence interval framework and then provides the criteria for "best" confidence intervals, along with the trade-offs between confidence and precision. Next, using a reader-friendly style with lots of worked out examples from various disciplines, he covers such pertinent topics as: the transformation principle whereby a confidence interval for a parameter may be used to construct an interval for any monotonic transformation of that parameter; confidence intervals on distributions whose shape changes with the value of the parameter being estimated;...
Smithson first introduces the basis of the confidence interval framework and then provides the criteria for "best" confidence intervals, along with th...
Probability Theory: A Primer intends to give a non-technical introduction to probability theory, as it is used in the social sciences. The topics covered include the concept of probability and its relation to relative frequency, the properties of probability, discrete and continuous random variables, and binomial, uniform, normal and chi-squared distributions. Readers who have taken basic college mathematics will be comfortable with this work, which frequently draws intuition and examples instead of technically involved arguments to make its points. In spite of the elementary level of...
Probability Theory: A Primer intends to give a non-technical introduction to probability theory, as it is used in the social sciences. The topics cove...
This book introduces fuzzy set theory to social science researchers. Fuzzy sets are categories with blurred boundaries. With classical sets, objects are either in the set or not, but objects can belong partially to more than one fuzzy set at a time. Many concepts in the social sciences have this characteristic, and fuzzy set theory provides methods for systematically dealing with them. A primary reason for not going beyond programmatic statements and rather unsophisticated uses of fuzzy set theory has been the lack of practical methods for combining fuzzy set concepts with statistical...
This book introduces fuzzy set theory to social science researchers. Fuzzy sets are categories with blurred boundaries. With classical sets, objects a...
Logistic Regression Models for Ordinal Response Variables provides applied researchers in the social, educational, and behavioral sciences with an accessible and comprehensive coverage of analyses for ordinal outcomes. The content builds on a review of logistic regression, and extends to details of the cumulative (proportional) odds, continuation ratio, and adjacent category models for ordinal data. Description and examples of partial proportional odds models are also provided. This book is highly readable, with lots of examples and in-depth explanations and interpretations of model...
Logistic Regression Models for Ordinal Response Variables provides applied researchers in the social, educational, and behavioral sciences with an acc...
This book examines ways to analyze complex surveys, and focuses on the problems of weights and design effects. This new edition incorporates recent practice of analyzing complex survey data, introduces the new analytic approach for categorical data analysis (logistic regression), reviews new software and provides an introduction to the model-based analysis that can be useful analyzing well-designed, relatively small-scale social surveys.
This book examines ways to analyze complex surveys, and focuses on the problems of weights and design effects. This new edition incorporates recent pr...
Polytomous Item Response Theory Models provides a unified, comprehensive introduction to the range of polytomous models available within item response theory (IRT). It begins by outlining the primary structural distinction between the two
Polytomous Item Response Theory Models provides a unified, comprehensive introduction to the range of polytomous models available within item response...
As budgets tighten and costs increase, it is becoming even more necessary that workable social programmes are shown to be worthy of support. This book presents one approach to evaluation -- multiattribute utility technology -- which stresses that evaluations should be comparative, and that all the different constituencies served by a programme and its different goals have to be kept in mind.
As budgets tighten and costs increase, it is becoming even more necessary that workable social programmes are shown to be worthy of support. This book...
