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

• Dex_scriptive 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 dex_scriptive 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 Dex_scriptive Statistics

Classification and Tabulation of Data

Graphical Representation of Classified Data

Summarizing Data: Averages

Summarizing Data: Dispersion

Summarizing Data: Skewness and Kurtosis

Dex_scriptive Statistics for Spatial Data

Dex_scriptive 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

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