Statistics and Research Methodology in Clinical Psychology

PAPER - III: Statistics and Research Methodology

Aim:

The aim of this paper is to elucidate various issues involved in conduct of a sound

experiment/survey. With suitable examples from behavioral field, introduce the trainees to the

menu of statistical tools available for their research, and to develop their understanding of the

conceptual bases of these tools. Tutorial work will involve exposure to the features available in a

large statistical package (SPSS) while at the same time reinforcing the concepts discussed in

lectures.

Objectives:

By the end of Part – II, trainees are required to demonstrate ability to:

1. Understand the empirical meaning of parameters in statistical models

2. Understand the scientific meaning of explaining variability

3. Understand experimental design issues - control of unwanted variability, confounding and bias.

4. Take account of relevant factors in deciding on appropriate methods and instruments to use in

specific research projects.

5. Understand the limitations and shortcomings of statistical models

6. Apply relevant design/statistical concepts in their own particular research projects.

7. Analyze data and interpret output in a scientifically meaningful way

8. Generate hypothesis/hypotheses about behavior and prepare a research protocol outlining the

methodology for an experiment/survey.

9. Critically review the literature to appreciate the theoretical and methodological issues involved.

RCI M.Phil Clinical Psychology Revised Syllabus 2009 50Academic Format of Units:

The course will be taught mainly in a mixed lecture/tutorial format, allowing trainees to participate

in collaborative discussion. Demonstration and hands-on experience with SPSS program are

desired activities.

Evaluation:

Theory - involving long and short essays, and problem-solving exercises

Syllabus:

Unit - I: Introduction: Various methods to ascertain knowledge, scientific method and its features;

problems in measurement in behavioral sciences; levels of measurement of psychological variables

- nominal, ordinal, interval and ratio scales; test construction - item analysis, concept and methods

of establishing reliability, validity and norms.

Unit - II: Sampling: Probability and non-probability; various methods of sampling - simple random,

stratified, systematic, cluster and multistage sampling; sampling and non-sampling errors and

methods of minimizing these errors.

Unit - III: Concept of probability: Probability distribution - normal, poisson, binomial; descriptive

statistics - central tendency, dispersion, skewness and kurtosis.

Unit - IV: Hypothesis testing: Formulation and types; null hypothesis, alternate hypothesis, type I

and type II errors, level of significance, power of the test, p-value. Concept of standard error and

confidence interval.

Unit - V: Tests of significance - Parametric tests: Requirements, "t" test, normal z-test, and "F" test

including post-hoc tests, one-way and two-way analysis of variance, analysis of covariance,

repeated measures analysis of variance, simple linear correlation and regression.

Unit – VI: Tests of significance - Non-parametric tests: Requirements, one sample tests – sign test,

sign rank test, median test, Mc Nemer test; two-sample test – Mann Whitney U test, Wilcoxon rank

sum test, Kolmogorov-Smirnov test, normal scores test, chi-square test; k sample tests - Kruskal

Wallies test, and Friedman test, Anderson darling test, Cramer-von Mises test.

Unit - VII: Experimental design: Randomization, replication, completely randomized design,

randomized block design, factorial design, crossover design, single subject design, non-

experimental design.

Unit - VIII: Epidemiological studies: Prospective and retrospective studies, case control and

cohort studies, rates, sensitivity, specificity, predictive values, Kappa statistics, odds ratio, relative

risk, population attributable risk, Mantel Haenzel test, prevalence, and incidence. Age specific,

disease specific and adjusted rates, standardization of rates. Tests of association, 2 x 2 and row x

column contingency tables.

Unit - IX: Multivariate analysis: Introduction, Multiple regression, logistic regression, factor

analysis, cluster analysis, discriminant function analysis, path analysis, MANOVA, Canonical

correlation, and Multidimensional scaling.

Unit - X: Sample size estimation: Sample size determination for estimation of mean, estimation of

proportion, comparing two means and comparing two proportions.

Unit - XI: Qualitative analysis of data: Content analysis, qualitative methods of psychosocial

research.

Unit - XII: Use of computers: Use of relevant statistical package in the field of behavioral science

and their limitations.

Essential References:

Research Methodology, Kothari, C. R. (2003). Wishwa Prakshan: New Delhi

Foundations of Behavioral Research, Kerlinger, F.N. (1995). Holt, Rinehart & Winston: USA

RCI M.Phil Clinical Psychology Revised Syllabus 2009 52Understanding Biostatistics, Hassart, T.H.

(1991). Mosby Year Book

Biostatistics: a foundation for analysis in health sciences, 8th ed, Daniel, W.W. (2005). John

Wiley and sons: USA

Multivariate analysis: Methods & Applications, Dillon, W.R. & Goldstein, M. (1984), John

Wiley & Sons: USA

Non-parametric statistics for the behavioral sciences, Siegal, S & Castellan, N.J. (1988).

McGraw Hill: New Delhi

Qualitative Research: Methods for the social sciences, 6th ed, Berg, B.L. (2007). Pearson

Education, USA