Medicine & Health Sciences

Statistical Methods in Psychiatry Research and SPSS
M. Venkataswamy Reddy, PhD

Statistical Methods in Psychiatry Research and SPSS

Published. Available now.
Pub Date: November 2014
Hardback Price: $139.95 US
Hard ISBN: 9781771880350
Pages: 350pp with index
Binding Type: hardbound

“Practicing physicians and psychiatrists, even those with academic pretensions, are often overwhelmed by study designs and statistical analysis. . . . The author [of this book] has recognized statistical needs of physicians and has attempted to present a simplified approach to statistics. The book provides an overview of psychiatric research, classifies statistical methods, describes types of data and variables, introduces quantitative and qualitative variables, elaborates study designs, discusses descriptive statistics, illuminates the basis of statistical inference, explains statistical tests of significance, and introduces correlational, multivariate, and meta-analysis. Each chapter focuses on a single aspect, introduces the issues, describes statistical theory, and provides examples. It also provides details of how to use the Statistical Package for Social Sciences (IBM SPSS Statistics) computer program for such analysis. The book is an attempt to fill the long felt need for a simple statistical text, useful for physicians and psychiatrists. . . . It will certainly help those who have a basic familiarity with statistical methods and analysis . . . . The book steps in the right direction for those who want to independently analyze and interpret data.”
—In Indian Journal of Psychiatry, by K. S. Jacob, Department of Psychiatry, Christian Medical College, Vellore, Tamil Nadu, India

This book has been prepared to help psychiatrists expand their knowledge of statistical methods and fills the gaps in their applications as well as introduces data analysis software. The book emphasizes the classification of fundamental statistical methods in psychiatry research that are precise and simple. Professionals in the field of mental health and allied subjects without any mathematical background can easily understand all the relevant statistical methods and carry out the analysis and interpret the results in their respective field without consulting any statistician.

The sequence of the chapters, the sections within the chapters, the subsections within the sections, and the points within the subsections have all been arranged to help professionals in classification refine their knowledge in statistical methods and fills the gaps if any.

Emphasizing simplicity, the fundamental statistical methods are demonstrated by means of arithmetical examples that may be reworked with pencil and paper in a matter of minutes, which will add to their perfection. The results of the rework have to be checked by using SPSS, and in this way professionals are introduced to this psychiatrist-friendly data analysis software.

Topics covered include:

  • an overview of psychiatry research
  • the organization and collection of data
  • descriptive statistics
  • the basis of statistical inference
  • tests of significance
  • correlational data analysis
  • multivariate data analysis
  • meta-analysis
  • reporting the results
  • statistical software
The language of the book is very simple and covers all aspects of statistical methods starting from organization and collection of data to descriptive statistics, statistical inference, multivariate analysis and meta-nalysis. There are two chapters on computer applications that deal with the most popular data analysis software: SPSS.

The book will be very valuable to professionals and post-graduate students in psychiatry and allied fields, such as psychiatric social work, clinical psychology, psychiatric nursing, and mental health education and mental health administration.


Chapter 1. Psychiatry Research
- 1.1 Research Questions in Psychiatry
- 1.2 Research Approaches
- 1.3 Protocol Writing for Quantitative Studies
- 1.4 Variables in Psychiatry
- 1.5 Statistical Methods in Psychiatry Research
Chapter 2. Observational Studies
- 2.1 Case-Series Analysis
- 2.2 Cross-Sectional Studies
- 2.3 Longitudinal Studies
Chapter 3. Experimental Studies
- 3.1 Basic Elements of Experiments
- 3.2 Parallel Control Clinical Trials
- 3.3 Further Control Clinical Trials
- 3.4 Informal Designs of Experiments
- 3.5 Formal Designs of Experiments
Chapter 4. One-Variable Descriptive Statistics
- 4.1 Classification and Tabulation of Data
- 4.2 Graphical Representation of Classified Data
- 4.3 Summarizing Data: Averages
- 4.4 Summarizing Data: Dispersion
- 4.5 Summarizing Data: Skewness and Kurtosis
- 4.6 Descriptive Statistics for Spatial Data
- 4.7 Descriptive Statistics for Time-Related Data
Chapter 5. Mental Health Statistics
- 5.1 Demographic Indicators
- 5.2 Demographic Indicators of India
- 5.3 Measures of Mental Morbidity
- 5.4 Mental Morbidity in India
- 5.5 Mental Health Delivery Systems in India
- 5.6 Mental Health Service Indicators
- 5.7 Service Indicators of Government Mental Hospitals
- 5.8 Service Indicators of General Hospital Psychiatry Units
Chapter 6. Probability and Probability Distributions
- 6.1 Probability Scale
- 6.2 Probability Distributions
Chapter 7. Sampling Theory and Methods
- 7.1 Theory of Sampling
- 7.2 Random Sampling Methods
- 7.3 Random Sampling Methods in Mental Morbidity Surveys
Chapter 8. Basic Elements of Statistical Inference
- 8.1 Basic Elements of Estimation of Parameters
- 8.2 Basic Elements of Tests of Significance
Chapter 9. Parametric Tests of Significance
- 9.1 One-Sample Parametric Tests
- 9.2 Two-Independent Sample Parametric Tests
- 9.3 Two-Related Sample Parametric Tests
Chapter 10. Experimental Data Analysis: ANOVA
- 10.1 One-Way ANOVA
- 10.2 Post-Hoc Multiple Comparison Tests: Scheffe Method
- 10.3 Two-Way ANOVA
- 10.4 22-Factorial ANOVA
- 10.5 Repeated Measures ANOVA
Chapter 11. Non-Parametric Tests of Significance
- 11.1 One-Sample Non-Parametric Tests
- 11.2 Two-Independent Sample Non-Parametric Tests
- 11.3 Two-Related Sample Non-Parametric Tests
- 11.4 K-Independent Sample Non-Parametric Tests
- 11.5 K-Related Sample Non-Parametric Tests
Chapter 12. Correlation Analysis and Regression Analysis
- 12.1 Two-Quantitative Variables Correlation Coefficients
- 12.2 Rank Correlation Coefficients
- 12.3 Two-Qualitative Variables Correlation Coefficients
- 12.4 Measures of Relative Risk
- 12.5 Regression Analysis
Chapter 13. Reliability Analysis and Validity Analysis
- 13.1 Scaling Techniques
- 13.2 Reliability Analysis
- 13.3 Validity Analysis
Chapter 14. Survival Analysis and Time Series Analysis
- 14.1 Survival Analysis
- 14.2 Time-Series Analysis
Chapter 15. Multivariate Statistical Methods
- 15.1 Profile Techniques
- 15.2 Multivariate Correlation Coefficients
- 15.3 Multiple Regression Analysis
- 15.4 Multivariate Analysis of Variance (MANOVA)
- 15.5 Analysis of Multi-Dimensional Contingency Tables
Chapter 16. Cluster Analysis
- 16.1 Functions of Cluster Analysis
- 16.2 Hierarchical Cluster Analysis
- 16.3 Measures of Similarity and Dissimilarity Between Persons
- 16.4 Hierarchical Agglomerative Clustering Methods
- 16.5 Determination of Number of Clusters
- 16.6 Partitioning Cluster Analysis
- 16.7 Validation of Resultant Clusters Numerical Demonstration
Chapter 17. Discriminant Analysis
- 17.1 Two-Groups Discriminant Analysis
- 17.2 K-Groups Discriminant Analysis Numerical Demonstration
Chapter 18. Factor Analysis
- 18.1 Basic Elements of Factor Analysis
- 18.2 Principal Components Analysis Numerical Demonstration
Chapter 19. Meta-Analysis
- 19.1 Location and Selection of Studies for Meta-Analysis
- 19.2 End-Points of Primary Studies
- 19.3 Quality Assessment of Selected Studies
- 19.4 Meta-Analysis Master Sheet
- 19.5 Meta-Analysis Plots
- 19.6 Methods for Pooling End-Points: Fixed Effects Model
- 19.7 Methods for Pooling End-Points: Random Effects Model
- 19.8 Additional Meta-Analysis Techniques
- 19.9 Implications of The Results of Meta-Analysis Numerical Demonstration
Chapter 20. Reporting The Results
- 20.1 Evaluation of The Study
- 20.2 Interpreting The Results
- 20.3 Writing The Report
Chapter 21. Statistical Packages for Social Sciences (SPSS)
- 21.1 SPSS Data Editor
- 21.2 Procedures for Entering Data in SPSS
- 21.3 Procedures To Run Data Analysis Using SPSS
- 21.4 Data Handling Using Data Menu
- 21.5 Data Handling Using Transform Menu
Chapter 22 Running Data Analysis Using SPSS
- 22.1 Running ‘Parametric Tests of Significance’
- 22.2 Running ‘ANOVA Tests of Significance’
- 22.3 Running ‘Non-Parametric Tests of Significance’
- 22.4 Running ‘Correlation Analysis and Regression Analysis’
- 22.5 Running ‘Reliability Analysis and Validity Analysis’
- 22.6 Running ‘Survival Analysis and Time Series Analysis’
- 22.7 Running ‘Multivariate Statistical Methods’
- 22.8 Running ‘Cluster Analysis and Discriminant Analysis’
- 22.9 Running ‘Factor Analysis’
Appendix 1: Basic Data of 40 Registered Patients at Nimhans
Appendix 2: A Classification of Statistical Methods
Appendix 3: Probability Distribution Tables

About the Authors / Editors:
M. Venkataswamy Reddy, PhD
Additional Professor of Biostatistics, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India

M. Venkataswamy Reddy is a permanent faculty member at National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India, and has over 30 years of teaching experience. He has published more than 20 scientific papers. His popular textbook, titled Statistics for Mental Health Care Research, is widely referred to by students and academicians alike. His main contributions include the development of suitable models for mental health delivery systems in India, meta-analysis for psychiatry research and STATA, and cluster analysis for psychiatry research and SPSS. He received an MSc in statistics from the Department of Statistics at Bangalore University; a DBS (PG diploma in Biostatistics) from ICMR’s Institute for Research in Medical Statistics, New Delhi; and a PhD in Biostatistics (topic: cluster formation in psychiatry with special reference to child psychiatry) from Bangalore University.

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