Multivariate Statistics and Modelling in Psychology I

Annotation: Statistical thinking in the development of psychology research methodology. Research designs, their characteristic hypotheses and research questions. Classification of statistical methods used in psychological research. Methods of univariate statistics and multivariate statistics. Basic concepts: variation, theoretical and statistical model. Literature: 1. Denis, D.J. (2015). Applied univariate, bivariate and multivariate statistics. Retrieved from https://ebookcentral-proquest-com.db.rsu.lv 2. Dekking, F. M., Kraaikamp, C., Lopuhaä, H. P., & Meester, L. E. (2005). A Modern Introduction to Probability and Statistics: Understanding why and how. Springer Science & Business Media.

Annotation: Psychometric parameters of measuring instruments and their compliance with psychometric requirements. Reliability and validity assessment methods. Quantitative tools for measuring variables selected for the doctoral thesis, analysis of their psychometric indicators. Topics covered during the class: 1. There are two main aspects of a scale's reliability. Describe these two aspects and how they are measured. What are the recommended minimum values for a scale to be considered reliable? Using a scale from your study, give details of its reliability including values reported in the literature. 2. There are many different types of validity discussed in relation to psychological scales and tests. Describe what you consider to be the four main types of scale validity. How is each of these aspects measured? Give examples from the scales that you will be using in your study. 3. Investigate the modern measurement tools of the variable selected in the doctoral thesis, find information about the psychometric parameters of these instruments, conduct the analysis of these parameters. Literature: 1. Li, H., Rosenthal, R., & Rubin, D. B. (1996). Reliability of measurement in psychology: From spearman-brown to maximal reliability. Psychological Methods, 1(1), 98-107. doi:http://dx.doi.org.db.rsu.lv/10.1037/1082-989X.1.1.98 2. Newton, P. E., & Shaw, S. D. (2013). Standards for talking and thinking about validity. Psychological Methods, 18(3), 301-319. doi:http://dx.doi.org.db.rsu.lv/10.1037/a0032969 3. Osburn, H. G. (2000). Coefficient alpha and related internal consistency reliability coefficients. Psychological Methods, 5(3), 343-355. doi:http://dx.doi.org.db.rsu.lv/10.1037/1082-989X.5.3.343 4. Raščevska, M. (2005). Psiholoģisko testu un aptauju konstruēšana un adaptācija. RaKa

Annotation: Revision of basic statistical tests used in modern psychology research: Descriptive statistics, hi square test, correlation analysis (Pearson, Spearman, partial correlation), t-test (and non–parametric equivalents U-test, Wilcoxon test). Conditions for the selection of statistical methods. Description of results (APA standard in English and Latvian). Topics covered during the class: Prepare information on the following basic statistical methods: Descriptive statistics, hi square test, correlation analysis (Pearson, Spearman, partial correlation), t-test (and non–parametric equivalents U-test, Wilcoxon test). For each of these techniques, answer the following questions: (a) What sort of research question is the technique designed to address? Use examples from your own scientific literature related to the doctoral thesis where possible. (b) How many variables are involved and what level of scaling is required (nominal, ordinal, interval etc.) for each variable? (c) What are the statistical assumptions (e.g., normal distribution of scores) underlying this approach? (d) What values (e.g., t-value) do you obtain from the analysis? What is the possible range of values? How do you interpret the results? (e) How would you present the results of the analysis in your report or thesis? Give examples from articles that you have obtained on the topic of your doctoral thesis. Literature: 1. Abbott, M.L. (2016). Using statistics in the social and health sciences with spss and excel. Retrievedfrom https://ebookcentral-proquest-com.db.rsu.lv 2. Nicol, A. A., & Pexman, P. M. (2010). Displaying your findings: A practical guide for creating figures, posters, and presentations. American Psychological Association. 3. Zinātniskās darbības metodoloģija: Starpdisciplināra perspektīva. Rīga: RSU, 2021 4. Scientific articles on the topic of the dissertation.

Annotation: Interpretation of statistical test results. The first and second type of errors in statistical hypothesis testing. Determination of statistical power, interpretation of significance level and confidence interval. Effect size indicators in psychological research. Literature: 1. Shuttleworth, M. & Wilson, L. T. (2008). Type I Error and Type II Error. Retrieved Feb 27, 2021 from Explorable.com: https://explorable.com/type-i-error 2. Dekking, F. M., Kraaikamp, C., Lopuhaä, H. P., & Meester, L. E. (2005). A Modern Introduction to Probability and Statistics: Understanding why and how. Springer Science & Business Media. 3. Goulet-Pelletier, J. C., & Cousineau, D. (2018). A review of effect sizes and their confidence intervals, part I: The Cohen's d family. The Quantitative Methods for Psychology, 14(4), 242-265. 4. Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in psychology, 4, 863.

Annotation: One-way, two-way ANOVA. Repeated-measures ANOVA, ANCOVA, MANOVA, MANCOVA. Topics covered during the class: 1. For which research designs is the appropriate method of analysis of variance applied? Give examples from research on the topic of the dissertation. 2. Which method of analysis of variance is appropriate for the specific task (data file)? Is the data set suitable for a specific analysis? Perform an analysis and draw sound conclusions. Literature: 1. David Giles. (2002). Advanced Research Methods in Psychology. Routledge. 2. The ultimate IBM® SPSS® Statistics guides. https://statistics.laerd.com/

Annotation: One-way, two-way ANOVA. Repeated-measures ANOVA, ANCOVA, MANOVA, MANCOVA. Topics covered during the class: 1. For which research designs is the appropriate method of analysis of variance applied? Give examples from research on the topic of the dissertation. 2. Which method of analysis of variance is appropriate for the specific task (data file)? Is the data set suitable for a specific analysis? Perform an analysis and draw sound conclusions. Literature: 1. David Giles. (2002). Advanced Research Methods in Psychology. Routledge. 2. The ultimate IBM® SPSS® Statistics guides. https://statistics.laerd.com/

Annotation: One-way, two-way ANOVA. Repeated-measures ANOVA, ANCOVA, MANOVA, MANCOVA. Topics covered during the class: 1. For which research designs is the appropriate method of analysis of variance applied? Give examples from research on the topic of the dissertation. 2. Which method of analysis of variance is appropriate for the specific task (data file)? Is the data set suitable for a specific analysis? Perform an analysis and draw sound conclusions. Literature: 1. David Giles. (2002). Advanced Research Methods in Psychology. Routledge. 2. The ultimate IBM® SPSS® Statistics guides. https://statistics.laerd.com/

Annotation: Application of cluster analysis and discriminant analysis in psychological research. Interpretation of results. K-Means Cluster, Hierarchical Cluster, and Two-Step Cluster. Literature: 1. Bardhoshi, G., Um, B., & Erford, B. T. (2020). Conducting a cluster analysis in counseling research: Four easy steps. Counseling Outcome Research and Evaluation, 1-9. 2. Clatworthy, J., Buick, D., Hankins, M., Weinman, J., & Horne, R. (2005). The use and reporting of cluster analysis in health psychology: A review. British journal of health psychology, 10(3), 329-358. 3. Zakharov, K. (2016). Application of k-means clustering in psychological studies. The quantitative methods for psychology, 12, 87-100. 4. Yim, O., & Ramdeen, K. T. (2015). Hierarchical cluster analysis: comparison of three linkage measures and application to psychological data. The quantitative methods for psychology, 11(1), 8-21.