Statistical Methods in Psychiatry Research and SPSS

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 fields without consulting a 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 fill 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. 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-analysis. Two chapters on computer applications 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 administration.

Preface Psychiatry Research Research Questions in Psychiatry Research Approaches Protocol Writing for Quantitative Studies Variables in Psychiatry Statistical Methods in Psychiatry Research Observational Studies Case-Series Analysis Cross-Sectional Studies Longitudinal Studies Experimental Studies Basic Elements of Experiments Parallel Control Clinical Trials Further Control Clinical Trials Informal Designs of Experiments Formal Designs of Experiments One-Variable Descriptive Statistics Classification and Tabulation of Data Graphical Representation of Classified Data Summarizing Data: Averages Summarizing Data: Dispersion Summarizing Data: Skewness and Kurtosis Descriptive Statistics for Spatial Data Descriptive Statistics for Time-Related Data Mental Health Statistics Demographic Indicators Demographic Indicators of India Measures of Mental Morbidity Mental Morbidity in India Mental Health Delivery Systems in India Mental Health Service Indicators Service Indicators of Government Mental Hospitals Service Indicators of General Hospital Psychiatry Units Probability and Probability Distributions Probability Scale Probability Distributions Sampling Theory and Methods Theory of Sampling Random Sampling Methods Random Sampling Methods in Mental Morbidity Surveys Basic Elements of Statistical Inference Basic Elements of Estimation of Parameters Basic Elements of Tests of Significance Parametric Tests of Significance One-Sample Parametric Tests Two-Independent Sample Parametric Tests Two-Related Sample Parametric Tests Experimental Data Analysis: ANOVA One-Way ANOVA Post-Hoc Multiple Comparison Tests: Scheffe Method Two-Way ANOVA 22-Factorial ANOVA Repeated Measures ANOVA Non-Parametric Tests of Significance One-Sample Non-Parametric Tests Two-Independent Sample Non-Parametric Tests Two-Related Sample Non-Parametric Tests K-Independent Sample Non-Parametric Tests K-Related Sample Non-Parametric Tests Correlation Analysis and Regression Analysis Two-Quantitative Variables Correlation Coefficients Rank Correlation Coefficients Two-Qualitative Variables Correlation Coefficients Measures of Relative Risk Regression Analysis Reliability Analysis and Validity Analysis Scaling Techniques Reliability Analysis Validity Analysis Survival Analysis and Time Series Analysis Survival Analysis Time-Series Analysis Multivariate Statistical Methods Profile Techniques Multivariate Correlation Coefficients Multiple Regression Analysis Multivariate Analysis of Variance (MANOVA) Analysis of Multi-Dimensional Contingency Tables Cluster Analysis Functions of Cluster Analysis Hierarchical Cluster Analysis Measures of Similarity and Dissimilarity Between Persons Hierarchical Agglomerative Clustering Methods Determination of Number of Clusters Partitioning Cluster Analysis Validation of Resultant Clusters Numerical Demonstration Discriminant Analysis Two-Groups Discriminant Analysis K-Groups Discriminant Analysis Numerical Demonstration Factor Analysis Basic Elements of Factor Analysis Principal Components Analysis Numerical Demonstration Meta-Analysis Location and Selection of Studies for Meta-Analysis End-Points of Primary Studies Quality Assessment of Selected Studies Meta-Analysis Master Sheet Meta-Analysis Plots Methods for Pooling End-Points: Fixed Effects Model Methods for Pooling End-Points: Random Effects Model Additional Meta-Analysis Techniques Implications of The Results of Meta-Analysis Numerical Demonstration Reporting The Results Evaluation of The Study Interpreting The Results Writing The Report Statistical Packages for Social Sciences (SPSS) SPSS Data Editor Procedures for Entering Data in SPSS Procedures To Run Data Analysis Using SPSS Data Handling Using Data Menu Data Handling Using Transform Menu Running Data Analysis Using SPSS Running ‘Parametric Tests of Significance’ Running ‘ANOVA Tests of Significance’ Running ‘Non-Parametric Tests of Significance’ Running ‘Correlation Analysis and Regression Analysis’ Running ‘Reliability Analysis and Validity Analysis’ Running ‘Survival Analysis and Time Series Analysis’ Running ‘Multivariate Statistical Methods’ Running ‘Cluster Analysis and Discriminant Analysis’ 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 Index

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.