Research Methods in Applied Settings

Research Methods in Applied Settings

An Integrated Approach to Design and Analysis

eBook - 2000
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Taylor
& Francis Publishing

Through its integrated approach to quantitative research methods, this text teaches readers how to plan, conduct, and write a research project and select and interpret data so they can become better consumers of research.  This is not a statistics book--there are very few formulas.  Rather, this book helps students master which statistic to use when and how to interpret the results.  Organized around the steps one takes in conducting a research project, this book is ideal for applied programs and for those who want to analyze and evaluate research articles. Having taught in a variety of departments, the authors have a good grasp of the research problems faced by master's and doctoral students in diverse areas of the behavioral and social sciences.

Text adopters applaud the book's clarity. Students are often confused by other texts' use of inconsistent terminology. To avoid this confusion, the authors present a semantically consistent picture that emphasizes five research approaches-- randomized experimental, quasi-experimental, comparative, associational, and descriptive.  The authors then show how these approaches lead to three kinds of research designs which, in turn, lead to three groups of statistics with the same names.  This consistent framework increases comprehension and the ability to apply the material.  Numerous applied problems, annotated examples, and diagrams and tables further promote comprehension. Although the book emphasizes quantitative research, the value of qualitative research is introduced.

This extensively revised edition features more than 50% new material including:

  • A new chapter on the evidence-based approach that emphasizes the importance of reporting confidence intervals and effect sizes and the increased use of meta-analysis.
  • An increased emphasis on evaluating research including an 8 step plan for evaluating research validity (Chs. 23 & 24) and its application to the 5 sample studies used throughout the book (Ch. 25).
  • Lots of practical advice on planning a research project (Ch. 2), data collection and coding (Ch. 15), writing the research report (Ch. 27), questions to use in evaluating a research article (Appendix E) and creating APA tables and figures (Appendix F).
  • A new chapter on non-experimental approaches/designs (Ch. 7) including qualitative research.
  • Web resources for students including critical thinking problems with answers and a sample outline of a research proposal.
  • An earlier and expanded introduction to measurement reliability and validity to further emphasize their differences and importance.
  • An extensively revised chapter on measurement validity consistent with the latest APA/AERA/NCME standards.
  • Fewer chapters on inferential statistics with an increased focus on how their selection is related to the design of the study and how to interpret the results using significance testing and effect sizes and confidence intervals.
  • Instructor's Resources with Power Points, test questions, answers to the application questions, and more.

Intended for graduate research or quantitative/experimental methods/design courses in psychology, education, human development and family studies, and other behavioral, social, business, and health sciences, independent sections and chapters can be read in ma
The authors of this unique text found that while most students can "crunch" the numbers quite easily and accurately with a calculator or computer, many have trouble seeing the "big picture" or seeing how research questions and design influence data analysis. As a result, the authors developed a semantically consistent framework that integrates traditional research approaches (experimental, quasi-experimental, comparative) into three basic kinds of research questions (difference, associational, and descriptive), which, in turn, lead to three kinds or groups of statistics with the same names.

This text:
*helps students become good consumers of research by demonstrating how to analyze and evaluate research articles;
*offers a number of summarizing diagrams and tables that clarify confusing or difficult to learn topics;
*points out the value of qualitative research and how it should lead quantitative researchers to be more flexible;
*divides all quantitative research questions into five logically consistent categories that help students select appropriate statistics and understand their cause and effect; and
*classifies design into three major types: between groups, within subjects, and mixed groups and shows that, although these three types use the same general type of statistics (e.g., ANOVA), the specific statistics in between-groups design are different from those in within-subjects and mixed groups.


Lea

The authors of this unique text found that while most students can "crunch" the numbers quite easily and accurately with a calculator or computer, many have trouble seeing the "big picture" or seeing how research questions and design influence data analysis. As a result, the authors developed a semantically consistent framework that integrates traditional research approaches (experimental, quasi-experimental, comparative) into three basic kinds of research questions (difference, associational, and descriptive), which, in turn, lead to three kinds or groups of statistics with the same names.

This text:
*helps students become good consumers of research by demonstrating how to analyze and evaluate research articles;
*offers a number of summarizing diagrams and tables that clarify confusing or difficult to learn topics;
*points out the value of qualitative research and how it should lead quantitative researchers to be more flexible;
*divides all quantitative research questions into five logically consistent categories that help students select appropriate statistics and understand their cause and effect; and
*classifies design into three major types: between groups, within subjects, and mixed groups and shows that, although these three types use the same general type of statistics (e.g., ANOVA), the specific statistics in between-groups design are different from those in within-subjects and mixed groups.


Publisher: Mahwah, N.J. : Lawrence Erlbaum, 2000
ISBN: 9780585330679
0585330670
Characteristics: 1 online resource (x, 465 p.) : ill
Additional Contributors: Morgan, George A. (George Arthur), 1936-

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