Clearly reviews the properties of important contemporary measures of association and correlation. Liebetrau devotes full chapters to measures for nominal, ordinal, and continuous (interval) data, paying special attention to the sampling distributions needed to determine levels of significance and confidence intervals. Valuable discussions also focus on the relationships between various measures, the sampling properties of their estimators and the comparative advantages and disadvantages of different approaches.
This revised edition of Schrodt's guide to microcomputer uSAGE for social scientists reflects the changes in systems, software and uSAGE which have taken place over the last three years. Schrodt adds material on: the Apple Macintosh system; the development of mainframe-quality statistical packages for micros; the development of Pascal and C as programming languages; the introduction of affordable desk-top publishing, graphics editing and RAM-resident utilities.
A presentation and critique of the use of multiple measures of theoretical concepts for the assessment of validity (using the multi-trait multi-method matrix) and reliability (using multiple indicators with a path analytic framework).
'The book is a good introduction, with practical examples and suggestions as to log-log plotting. There is even a footnote reminding one of the basic arithmetic of logarithms! There are examples, validity studies and several suggestions as to the value of line marking as a questionnaire response mode. In all a valuable informative addition to an important series.' -- Quantitative Sociology Newsletter
This Family Report was developed for use in conjunction with the AEPS (R) for children 3 to 6 years to obtain information from parents and other caregivers about their childrens skills and abilities across major areas of development.
Unlike other types of qualitative research, the clinical perspective in field research does not aim to be impartial and uninvolved. The clinician is usually a consultant brought in specifically to effect change in an organization, and therefore works under a very different set of technical and ethical restraints. Edgar Schein succinctly outlines the clinical perspective in field research, how it differs from other types of qualitative research and its inherent rewards and difficulties.
While much has been written on alternative paradigm research, there is little concrete advice on how to effectively use the theoretical notions of naturalistic inquiry in practice. Doing Naturalistic Inquiry is the practical guide designed to help beginning researchers apply the constructivist paradigm. Based upon the theoretical work of Lincoln and Guba in developing the naturalistic-or constructivist--paradigm, Erlandson and his colleagues show readers how these ideas shape the practice of conducting alternative paradigm research. The book covers the research process from design through data collection analysis and presentation and examines important issues generally minimized in positivist research texts ethics, trustworthiness, and authenticity. Cases from a wide variety of disciplines demonstrate the efficacy of the methods described. Doing Naturalistic Inquiry is a highly useful teaching tool for anyone using a constructivist lens on research.
Meta-Analysis shows concisely, yet comprehensively, how to apply statistical methods to achieve a literature review of a common research domain. It demonstrates the use of combined tests and measures of effect size to synthesize quantitatively the results of independent studies for both group differences and correlations. Strengths and weaknesses of alternative approaches, as well as of meta-analysis in general, are presented.
This monograph is not statistical. It looks instead at pre-statistical assumptions about dependent variables and causal order. Professor Davis spells out the logical principles that underlie our ideas of causality and explains how to discover causal direction, irrespective of the statistical technique used. He stresses throughout that knowledge of the `real world' is important and repeatedly challenges the myth that causal problems can be solved by statistical calculations alone.
