Social Work Research Methods
From Conceptualization to Dissemination
Published on 16. October 2007
Book
Hardback
480 pages
978-0-205-46097-7 (ISBN)
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Description
Social Work Research Methods is a stand alone "how-to" social research text that covers conceptualization, design, implementation, data management, and statistical analysis with comprehensively detailed examples.
It provides students with everything they need to learn about social science research, and how complete a research project from start to finish. In addition, the text's research process is covered sequentially, in a straightforward "how-to" format. It discusses values and ethics, conceptualization, design, familiarization with key computer programs (Microsoft Excel, SAS, SPSS and NVIVO), analyses, implementation and dissemination. It is also written in a tone that is intentionally light-hearted to increase student interest and comfort level by addressing often overlooked aspects of conducting research (e.g. data management, IRB clearance, and grant development) in detail.
Key highlights of the text include five example research projects. These example projects are presented in their entirety; including how the researchers chose their areas of interest, how they executed their literature reviews (annotated citation lists are given), and how they designed, implemented, and disseminated (poster, article, agency report, or PowerPoint presentation) their work.
It provides students with everything they need to learn about social science research, and how complete a research project from start to finish. In addition, the text's research process is covered sequentially, in a straightforward "how-to" format. It discusses values and ethics, conceptualization, design, familiarization with key computer programs (Microsoft Excel, SAS, SPSS and NVIVO), analyses, implementation and dissemination. It is also written in a tone that is intentionally light-hearted to increase student interest and comfort level by addressing often overlooked aspects of conducting research (e.g. data management, IRB clearance, and grant development) in detail.
Key highlights of the text include five example research projects. These example projects are presented in their entirety; including how the researchers chose their areas of interest, how they executed their literature reviews (annotated citation lists are given), and how they designed, implemented, and disseminated (poster, article, agency report, or PowerPoint presentation) their work.
More details
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 286 mm
Width: 221 mm
Thickness: 23 mm
Weight
1220 gr
ISBN-13
978-0-205-46097-7 (9780205460977)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Content
Table of Contents
Chapter 1: Introduction
Section 1: Definitions
Section 2: The Ethics of Social Science
Section 3: The Process of Doing Social Science
Section 4: The Role of Theory
Chapter 2: Values and Ethics
Section 1: Definitions
Section 2: Personal Values and Research
Section 3: Examples From History: Harm to Human Subjects
Section 4: Examples From History: Other Issues
Section 5: Professional Codes of Ethics: Human Subjects
Section 6: Professional Codes of Ethics: Other Issues
Chapter 3: Specification
Section 1: Specification
Section 2: Your Area of Interest
Section 3: The Initial Literature Review
Section 4: Reviewing the Field
Section 5: Understanding Your Literature
Section 6: Your Conceptual Framework
Section 7: Formalizing and Presenting Your Conceptual Framework
Chapter 4: Design
Section 1: Specifying your Aims, Question and Hypotheses
Section 2: Seven Key Dimensions of Research Design
Section 2.1: Purpose
Section 2.2: Causality and Control
Section 2.3: Subjects and Sampling
Section 2.4: Assignment of Subjects to Different Groups or Conditions
Section 2.5: Investigator Manipulation
Section 2.6: Timeframe
Section 2.7: Data Type
Section 3: Internal Validity and Research Design
Section 4: Finalizing the Design
Section 5: True Experimental Designs in Detail
Section 6: Quasi-Experimental Designs in Detail
Section 7: Nonexperimental Designs in Detail
Section 8: Human Subjects, IRB's and Ethics
Section 9: Summary of Key Design Products
Chapter 5: Measurement
Section 1: Measureent and Data Type
Section 2: Reliability and Validity
Section 3: Administration of Instruments
Section 4: Structure of Instruments
Section 5: Choosing a Measure
Chapter 6: Qualitative Research
Section 1: Qualitative Research Defined
Section 2: Paradigms and Frameworks in Qualitative Research
Section 3: Collecting Data in Qualitative Research
Section 4: Analysis in Qualitative Research
Chapter 7: Clinical Multisubject Research
Section 1: Introduction
Section 2: Needs Assessment and Caseload Analysis
Section 3: Program Monitoring
Section 4: Outcome Evaluation
Chapter 8: Clinical Single-Subject Research
Section 1: Why Study Individuals in Your Practice?
Section 2: Review of Key Terms in Single Subject Designs
Section 3: Treatment Goals and Outcomes
Section 4: Choosing a Way to Measure Outcomes
Section 4.1: Outcomes as Observed Behaviors
Section 4.2: Asking the Client or Someone Else (Finding and Using Existing Measures)
Section 4.3: Asking the Client or Someone Else (Creating Measures)
Section 4.4: Checking the Record (Administrative, Archival or Similar Data)
Section 5: Choosing and Implementing a Design
Section 5.1: The Basic Quasi-Experimental Approach (A B)
Section 5.2: Quasi-Experimental Approaches with Follow-up (A B A)
Section 5.3: Multiple-Baseline Models (A B A B)
Section 5.4: Multiple-Intervention Models (A B C)
Section 5.5: Combined Intervention Models (A B B+C)
Section 6: Timeframes
Section 7: Analysis, Interpretation and Dissemination
Chapter 9: Design Examples
Section 1: Kathy
Section 2: Maria
Section 3: Abigail
Section 4: Yuan
Section 5: John
Chapter 10: Computers in Social Science Research
Section 1: Spreadsheets (Excel)
Section 2: Statstical Analyis Software (SPSS)
Section 3: Statistical Analyis Software (SAS)
Section 4: Qualitative Analysis Software (NVivo)
Chapter 11: Implementation
Section 1: Pilot Studies: Bridging Design and Full-Scale Implementation
Section 2 Implementation Tasks
Section 2.1: Getting Ready
Section 2.2: Getting Agreements with Partners
Section 2.3: Getting Access to Your Sample
Section 2.4: Obtaining Human Subjects Clearance
Section 2.5: Obtaining Funding
Section 2.6: Getting Materials Ready
Section 2.7: Getting Personnel
Section 2.8: Formalizing Data Collection (Codebooks)
Section 2.9: Training Personnel
Section 3 Monitoring The Process
Section 3.1: Monitoring Data Collection
Section 3.2: Monitoring Contamination
Section 3.3: Monitoring Fidelity
Section 3.4: Monitoring Other Potential Problems
Section 4: Data Management
Section 4.1: Data Procurement
Section 4.2: Transferring Data to an Electronic Format
Section 4.3: Creating New Variables
Chapter 12: Implementation Examples
Section 1: Kathy
Section 2: Maria
Section 3: Abigail
Section 4: Yuan
Section 5: John
Chapter 13: Quantitative Analysis
Section 1: Important Terms
Section 2: Checking Your Data
Section 3: Univariate Statistics
Section 4: How We Explore Data and Test Hypotheses
Section 5: Basic Statistical Tests
Section 5.1: Tests of Association
Section 5.11: Bivariate Categorical Tests
Section 5.12: Correlation
Section 5.2: Tests of Difference
Section 5.21: T-Tests
Section 5.22: One-Way ANOVA
Section 5.11: Factorial ANOVA or Two-Way ANOVA
Section 6: An Introduction to Regression
Chapter 14: Moving On in Quantitative Analysis
Section 1: Advanced Applications of Correlation: Multiple Regression
Section 2: Principal Components Analysis
Section 3: ANCOVA & MANOVA: Combining Ideas of Regression and ANOVA
Section 4: Introduction to Advanced Categorical Analyses
Section 5: Logistic Regression
Section 6: Controlling For Time
Section 7: Categorical Time to Event Analyses
Section 8: Special Issues
Section 5.1: Clustering of Observations
Section 5.2: Correlations Over Time
Section 5.21: Complex Data Sets, GIS and Other Analytic Needs
Chapter 15 Analysis Examples
Section 1: Kathy
Section 2: Maria
Section 3: Abigail
Section 4: Yuan
Section 5: John
Chapter 16: Interpretation & Dissemination
Section 1: Four Components of Scientific Reporting
Section 2: Different Audiences
Section 3: Different Types of Products
Section 4: Practical Advice for Getting Presentations and Articles Accepted
Appendix: Grant Examples
Foundation Grant Example
NSF Grant Example
Chapter 1: Introduction
Section 1: Definitions
Section 2: The Ethics of Social Science
Section 3: The Process of Doing Social Science
Section 4: The Role of Theory
Chapter 2: Values and Ethics
Section 1: Definitions
Section 2: Personal Values and Research
Section 3: Examples From History: Harm to Human Subjects
Section 4: Examples From History: Other Issues
Section 5: Professional Codes of Ethics: Human Subjects
Section 6: Professional Codes of Ethics: Other Issues
Chapter 3: Specification
Section 1: Specification
Section 2: Your Area of Interest
Section 3: The Initial Literature Review
Section 4: Reviewing the Field
Section 5: Understanding Your Literature
Section 6: Your Conceptual Framework
Section 7: Formalizing and Presenting Your Conceptual Framework
Chapter 4: Design
Section 1: Specifying your Aims, Question and Hypotheses
Section 2: Seven Key Dimensions of Research Design
Section 2.1: Purpose
Section 2.2: Causality and Control
Section 2.3: Subjects and Sampling
Section 2.4: Assignment of Subjects to Different Groups or Conditions
Section 2.5: Investigator Manipulation
Section 2.6: Timeframe
Section 2.7: Data Type
Section 3: Internal Validity and Research Design
Section 4: Finalizing the Design
Section 5: True Experimental Designs in Detail
Section 6: Quasi-Experimental Designs in Detail
Section 7: Nonexperimental Designs in Detail
Section 8: Human Subjects, IRB's and Ethics
Section 9: Summary of Key Design Products
Chapter 5: Measurement
Section 1: Measureent and Data Type
Section 2: Reliability and Validity
Section 3: Administration of Instruments
Section 4: Structure of Instruments
Section 5: Choosing a Measure
Chapter 6: Qualitative Research
Section 1: Qualitative Research Defined
Section 2: Paradigms and Frameworks in Qualitative Research
Section 3: Collecting Data in Qualitative Research
Section 4: Analysis in Qualitative Research
Chapter 7: Clinical Multisubject Research
Section 1: Introduction
Section 2: Needs Assessment and Caseload Analysis
Section 3: Program Monitoring
Section 4: Outcome Evaluation
Chapter 8: Clinical Single-Subject Research
Section 1: Why Study Individuals in Your Practice?
Section 2: Review of Key Terms in Single Subject Designs
Section 3: Treatment Goals and Outcomes
Section 4: Choosing a Way to Measure Outcomes
Section 4.1: Outcomes as Observed Behaviors
Section 4.2: Asking the Client or Someone Else (Finding and Using Existing Measures)
Section 4.3: Asking the Client or Someone Else (Creating Measures)
Section 4.4: Checking the Record (Administrative, Archival or Similar Data)
Section 5: Choosing and Implementing a Design
Section 5.1: The Basic Quasi-Experimental Approach (A B)
Section 5.2: Quasi-Experimental Approaches with Follow-up (A B A)
Section 5.3: Multiple-Baseline Models (A B A B)
Section 5.4: Multiple-Intervention Models (A B C)
Section 5.5: Combined Intervention Models (A B B+C)
Section 6: Timeframes
Section 7: Analysis, Interpretation and Dissemination
Chapter 9: Design Examples
Section 1: Kathy
Section 2: Maria
Section 3: Abigail
Section 4: Yuan
Section 5: John
Chapter 10: Computers in Social Science Research
Section 1: Spreadsheets (Excel)
Section 2: Statstical Analyis Software (SPSS)
Section 3: Statistical Analyis Software (SAS)
Section 4: Qualitative Analysis Software (NVivo)
Chapter 11: Implementation
Section 1: Pilot Studies: Bridging Design and Full-Scale Implementation
Section 2 Implementation Tasks
Section 2.1: Getting Ready
Section 2.2: Getting Agreements with Partners
Section 2.3: Getting Access to Your Sample
Section 2.4: Obtaining Human Subjects Clearance
Section 2.5: Obtaining Funding
Section 2.6: Getting Materials Ready
Section 2.7: Getting Personnel
Section 2.8: Formalizing Data Collection (Codebooks)
Section 2.9: Training Personnel
Section 3 Monitoring The Process
Section 3.1: Monitoring Data Collection
Section 3.2: Monitoring Contamination
Section 3.3: Monitoring Fidelity
Section 3.4: Monitoring Other Potential Problems
Section 4: Data Management
Section 4.1: Data Procurement
Section 4.2: Transferring Data to an Electronic Format
Section 4.3: Creating New Variables
Chapter 12: Implementation Examples
Section 1: Kathy
Section 2: Maria
Section 3: Abigail
Section 4: Yuan
Section 5: John
Chapter 13: Quantitative Analysis
Section 1: Important Terms
Section 2: Checking Your Data
Section 3: Univariate Statistics
Section 4: How We Explore Data and Test Hypotheses
Section 5: Basic Statistical Tests
Section 5.1: Tests of Association
Section 5.11: Bivariate Categorical Tests
Section 5.12: Correlation
Section 5.2: Tests of Difference
Section 5.21: T-Tests
Section 5.22: One-Way ANOVA
Section 5.11: Factorial ANOVA or Two-Way ANOVA
Section 6: An Introduction to Regression
Chapter 14: Moving On in Quantitative Analysis
Section 1: Advanced Applications of Correlation: Multiple Regression
Section 2: Principal Components Analysis
Section 3: ANCOVA & MANOVA: Combining Ideas of Regression and ANOVA
Section 4: Introduction to Advanced Categorical Analyses
Section 5: Logistic Regression
Section 6: Controlling For Time
Section 7: Categorical Time to Event Analyses
Section 8: Special Issues
Section 5.1: Clustering of Observations
Section 5.2: Correlations Over Time
Section 5.21: Complex Data Sets, GIS and Other Analytic Needs
Chapter 15 Analysis Examples
Section 1: Kathy
Section 2: Maria
Section 3: Abigail
Section 4: Yuan
Section 5: John
Chapter 16: Interpretation & Dissemination
Section 1: Four Components of Scientific Reporting
Section 2: Different Audiences
Section 3: Different Types of Products
Section 4: Practical Advice for Getting Presentations and Articles Accepted
Appendix: Grant Examples
Foundation Grant Example
NSF Grant Example