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Spatial Regression Models illustrates the use of spatial analysis in the social sciences within a regression framework and is accessible to readers with no prior background in …
In Methods of Randomization in Experimental Design, author Valentim R. Alferes presents the main procedures of random assignment and local control in between-subjects experimental …
Sample design is key to all surveys, fundamental to data collection, and to the analysis and interpretation of the data. Introduction to Survey Sampling, Second Edition provides an …
Fuzzy set theory deals with sets or categories whose boundaries are blurry or, in other words, "fuzzy." This book presents an accessible introduction to fuzzy set theory, focusing …
Latent growth curve modeling (LGM)—a special case of confirmatory factor analysis designed to model change over time—is an indispensable and increasingly ubiquitous approach for …
This volume covers the commonly ignored topic of heteroskedasticity (unequal error variances) in regression analyses and provides a practical guide for how to proceed in terms of …
"Brown is well known for research on mathematical modeling in the social sciences. His book introduces the graph algebra approach to modeling systems in the social …
A presentation and critique of the use of multiple measures of theoretical concepts to assess both validity, using the multirait-multimethod matrix, and reliablity, using multiple …
Carol A. Chapelle shows readers how to design validation research for tests of human capacities and performance. Any test that is used to make decisions about people or programs …
Clearly reviews the properities of important contemporary measures of association and correlation. Devotes full chapters to measures for nominal, ordinal, and continuous data, …