A Research Primer for the Social and Behavioral Sciences - 1st Edition - ISBN: 9780123041807, 9781483258010

A Research Primer for the Social and Behavioral Sciences

1st Edition

Authors: Miriam Schapiro Grosof Hyman Sardy
eBook ISBN: 9781483258010
Imprint: Academic Press
Published Date: 8th October 1985
Page Count: 450
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Description

A Research Primer for the Social and Behavioral Sciences provides an introductory but comprehensive overview of the research process that primarily concerns human subjects.

This book discusses the methods of acquiring knowledge, importance of a well-chosen problem, review of the literature, and relationship between theory-building and hypothesis-testing. The common sources of invalidity in practice, non-experimental research types, Stevens' classification of scales, and estimation based on probabilistic sampling are also elaborated. This text likewise covers the role of computer in research, techniques for analysis of data, univariate and bivariate statistics, and assumptions underlying analysis of variance. Other topics include the canonical correlation analysis, non-parametric analysis of variance, deterministic problem analysis techniques, and common errors in presentation of findings.

This publication is intended for novice investigators in the broad category of social and behavioral sciences.

Table of Contents


Preface

Acknowledgments

Introduction

Appendix: Decision Trees

Notes

1. Preliminaries

Introduction

Methods of Acquiring Knowledge

The Scientific Method

Identifying a Problem as Researchable

The Role of Theory

Causality

Controlled Observations

Statistical Analysis

Overview of the Scientific Method

Classification of Research

Formulative and Verificational Research

Basic, Applied, and Action Research

Notes

Additional Reading

2. Choosing the Research Problem and Stating the Problem-Question

The Importance of a Well-Chosen Problem

Sources of Problems

The Role of Curiosity

A Theoretical Basis for the Study

Originality

Amenability to Replication

Practical Aspects of Problem Formulation

Time

Costs

Availability of Other Resources

Availability of Information

Usefulness of the Findings

Politics of Problem Selection

Political Problems Peculiar to Doctoral Students: The Committee

Capabilities and Limitations of the Researcher

Stating the Problem-Question: Avoiding Common Errors in Formulation

A Research Plan

Design: Preliminaries

Trouble: The Best-Laid Plans

Appendix: Difficulties Nobody Mentions Because They Figure You Shouldn't Have To Be Told (Maybe You Don't)

Notes

Additional Reading

3. The Background of the Problem: Review of the Literature

Introduction

Locating Reference Materials: Bibliographic

Reviewing and Abstracting

Checklist for Evaluating the Report of a Study

Locating Reference Materials: Other Researchers

Format: Notes and Bibliography

Recording and Storing Bibliographic Material

When to Stop

Common Errors

Outcome of the Background Search

Appendix: Research Indexes

Notes

Additional Reading

4. Definitions and Major Research Hypotheses

Introduction: The Relationship Between Theory-Building and Hypothesis-Testing

Role of Definitions in Hypothesis Formulation

Selection of Variables and Identification of Their Role in the Hypothesis

The Hypothesis: What Is It?

Stating the Expected Relationships

Operationalizing Definitions and Hypotheses

The Logic of Hypothesis Testing

The Null Hypothesis

Level of Significance, Region of Rejection, and Type I or α-Error

Type II or β-Error

One-Tailed Versus Two-Tailed Tests (Directional Versus Nondirectional Effects)

When Significance Tests Are Not Appropriate or Useful

A Final Word

Notes

Additional Reading

5. Evaluating Method and Design

Introduction

Classification of Research

Control

Internal and External Validity

Control of Variance

Common Sources of Invalidity in Practice

Notes

Additional Reading

6. Research Types

Introduction

Nonexperimental Research Types: Historical

Nonexperimental Research Types: Descriptive

1. Longitudinal Studies

2. Case and Generalized Case Studies

3. Correlational Studies

4. System Studies

Experimental Research Types

Overlapping Research Types

Pilot Studies

Summary

Notes

Additional Reading

7. Procedure: Measurement, Instrumentation, and Data Collection

Introduction

Measurement

Stevens' Classification of Scales

Other Ways to Classify Scales

Scales and Statistics

Instruments

Direct Observation

Equipment

Questions and Schedules

Some Vocabulary

Questions

Scaling: Constructing Scales

Indexes

Normative and Ipsative Scoring

Criteria for Evaluating Instruments

Validity

Reliability

Standardization

Sensitivity and Differentiability

The Role of Measurement and Instrumentation

Problems of Developing Your Own Instrument

Notes

Additional Reading

8. The Study Population: Sampling

Introduction

Sampling: Advantages and Disadvantages

Nonprobability Sample Types

Estimation Based on Probabilistic Sampling

Determining a Sampling Procedure: Initial Steps

Sampling Types

Simple Random Sampling

Stratified Sampling

Systematic Sampling

Cluster Sampling

Matched Samples

Two-Phased Sampling

Sequential Sampling

Interpenetrating Replicate Subsampling

Other Sampling Types

Determining Sample Size

Sampling Errors to Avoid

Sampling and Studying Human Populations

Sampling and External Validity: A Concluding Note

Notes

Additional Reading

9. Role of Computer in Research

Computer Processing of Data

Some Basic Computer Terminology

Access to Computing Facilities

Who Processes Your Data?

Computer Costs

Timely Processing

Coding and Documentation

Computerizing Input Information

Verification of Input Information

Security of Machine-Readable Information

Automated Data Acquisition and Process Control

Data Base Management (Management Information) Systems and Computer Simulation (Automated Data Generation)

Your Own Software

Computer Packages for the Social Sciences

Computer Graphics

Text Editors

Keeping Data Records (Archiving)

Notes

Additional Reading

10. Techniques for Analysis of Data

Introduction

A Note on Word Usage

Questions That Data Analysis Can and Cannot Answer

Experts

Choosing and Using a Statistical Resource Person or Consultant

Choosing and Using a Computer Resource Person

Classification of Data Analysis or Statistical Techniques

Evaluating Competing Procedures

Computer Use

Decision Trees for Choosing Statistical Procedures

Notes

Additional Reading

11. Probabilistic Methods: Univariate and Bivariate Statistics

Introduction

Graphs and Charts

Bar Charts

Line Plots or Line Charts

Scattergrams

Pie Charts

Exploratory Graphing Techniques

Statistical Maps

Miscellaneous Schematic Graphs

Tables

Percentages

Cross Sorts and Cross Breaks

Univariate Measures and Techniques

The Measurement of Difference

Measurement of Relationships and Strength of Association Nonparametric Relationships

Afterword

Notes

Additional Reading

12. Probabilistic Methods: Multivariate Statistics I: Basic Strategies

Introduction

Charts and Tables for Three or More Variables

Multiple Causality

Partial and Semipartial (Part) Correlation

Multiple Regression Analysis

Least Squares Assumptions

Nonlinear Regression: Transforming (Re-Expressing) Variables

Path Analysis

The Analysis of Variance (ANOVA)

Assumptions Underlying Analysis of Variance

n-Uily Analysis of Variance and Factorial Design

Other Types of Design

Analysis of Covariance (ANCOVA)

Multiple Comparison Procedures

Notes

Additional Reading

13. Probabilistic Methods: Multivariate Statistics II: Clustering and Classification Techniques

Introduction

Factor Analysis

Discriminant Analysis

Assumptions and Procedures

Interpreting Discriminant Functions

Classification of Cases

Calculating Procedures

A Last Word on Discriminant Analysis

Canonical Correlation Analysis

Multivariate Linear Methods: Some Comparisons

Notes

Additional Reading

14. Probabilistic Methods: Multivariate Statistics III: Techniques Free of Linear Assumptions

Introduction

Time Series: Special Issues in Bivariate and Multivariate Analyses

Nonparametric Multivariate Methods

Introduction

Nonparametric Analysis of Variance (Kruskal-Uilllis and Friedman Tests)

The Coefficient of Concordance

Cochran's Q Test

The Chi-Square Tests

Partialling Procedures

Some Last Thoughts on Multivariate Statistical Techniques

Notes

Additional Reading

15. Deterministic Problem Analysis Techniques

Introduction

Elementary Mathematical Techniques

Calculus Based Techniques

Mathematical Programming

Linear Programming

Integer Programming

Parametric Programming (Sensitivity Analysis)

Nonlinear Programming

Dynamic Programming

Network Models

PERT

Critical Path Method (CPM)

Decision Theory

Finite Markov Chain Processes

Inventory Models

Waiting Line (Queueing) Models

Afterword

Notes

Additional Reading

16. Endgame

Evaluating the Design of Your Study

The Overall Structure of the Report

Review of Related Literature: Suggesting the Importance of the Study

Presentation of Design and Methodology

What To Make of It

The Statement of Findings

What Are Findings?

Presentation of Findings

Common Errors in Presentation of Findings

Your Conclusions

Recapitulation of Problem Statement

Critical Comment: Implications and (General) Discussion

Resolution of Contradictions

Negative Results

Your Summary

Journal Articles: Special Considerations

Evaluation Reports: Special Considerations

Pitfulls in Presentation of Conclusions

The Research Report: Recapitulation

Developing a Readable Style

Afterword

Appendix: Dissertation Checklist

Notes

Additional Reading

References

Index

Details

No. of pages:
450
Language:
English
Copyright:
© Academic Press 1985
Published:
Imprint:
Academic Press
eBook ISBN:
9781483258010

About the Author

Miriam Schapiro Grosof

Hyman Sardy