<- Back to MMX9120

Issues in Study Design

Petri Nokelainen (petri.nokelainen@tuni.fi)

Learning material

Lectures [PPT]

Articles

1. Cross-sectional multilevel modeling

2. Experience sampling

3. t-test, M-W U-test, regression analysis, ANOVA

4. Chi-square test, ANOVA, EFA

5. Path analysis, CFA

Readings

Abelson, R. P. (1995). Statistics as Principled Argument. Hillsdale, NJ: Lawrence Erlbaum Associates.

Booth, W. C., Colomb, G. G., Williams, J. M., Bizup, J., & Fitzgerald, W. T. (2016). The Craft of Research. Fourth edition. Chicago: The University of Chicago Press.

Jackson, S. (2006). Research Methods and Statistics. A Critical Thinking Approach. Second edition. Belmont, CS: Thomson.

Bannan-Ritland, B. (2003). The Role of Design in Research: The Integrative Learning Design Framework. Educational Researcher, 32(1), 21-24.

Tabachnick, B., & Fidell, L. (2013). Using Multivariate Statistics. Sixth edition. Essex: Pearson.

Thiese, M. (2014). Observational and interventional study design types; an overview. Biochemia Medica, 24(2), 199-210.

Tirri, K., Nokelainen, P., & Komulainen, E. (2013). Multiple intelligences: Can they be measured? Psychological Test and Assessment Modeling, 55(4), 438-461.

Wasserman, L. (2004). All of Statistics. A Concise Course in Statistical Inference. New York: Springer.

Wickrama, K., Kyoung Lee, T., Walker O’Neal, C., & Lorenz, F. (2016). Higher Order Growth Curves and Mixture Modeling with Mplus. New York: Routledge.

External learning material

Different types of variables
categorical (nominal, ordinal) and continuous (interval, ratio), independent (IV) and dependent (DV)

To compare differences between groups
two groups: t-test (normal distribution) or Mann-Whitney U-test (non-normal distribution)
more than two groups: Analysis of variance (ANOVA, normal distribution) or Kruskal-Wallis H-test (non-normal distribution)
multivariate approach to analyse differences between groups and predict group membership: linear discriminant analysis (multivariate normal distributions, linear relationships)

To investigate associations between variables
correlation: Pearson product moment (interval or ratio scale, normal distribution, linear relationship, no outliers) or Spearman rank order (ordinal, interval or ratio scale, monotonous relationship)

To predict dependent variable values
regression: linear (interval or ratio scale, normal distribution, linear relationship, no outliers) or logistic (DV: dichotomous, IV(s): categorical or continuous, linear relationship between DV and IV(s))

To reduce number of variables
principal component analysis

Assignment

1. Write a 2000 word essay where you evaluate the design approaches of three articles that you have selected. Minimum requirement is that you base your evaluation on the lecture material, but you are encouraged to use other sources (e.g., books or articles provided in the lecture). The essay should begin with a short overview of the three selected articles (e.g., describing their topic, research questions) and then provide analysis of their designs (e.g., cross-sectional or longitudinal design, what kind of samples and methods are used to answer to the research questions). You need to create a reference list at the end of the essay and have in-text citations in APA style.