Week 6 - Quantitative Research Methods Flashcards
- Understand the two major approaches to inferential statistics - Differences between univariate and multivariate statistics - What is General Linear Model - Familiarity with different types of analytic methods
What are the two major data analytic approaches in psychological research?
- exploring relationships between variables
- comparing groups
what analyses are used to conduct statistical analyses to explore relationships?
- correlation / partial correlation
structure: cluster analysis, factor analysis, multidimensional scaling (MDS)
prediction: multiple regression (continuous), logistic regression (dichotomous)
casual links: modelling techniques (path analysis, confirmatory factor analysis, structural equation modelling (SEM), hierarchical linear modelling)
what analyses are used to conduct statistical; analyses to compare groups?
- t-tests
- analysis of variance (ANOVA)
- analysis of covariance (ANCOVA) / multivariate analysis of variance (MANOVA)
- discriminant analysis
what is the difference between univariate statistics and multivariate statistics?
- multivariate statistics involve multiple IVs and/or DVs (outcome/s)
- univariate statistics involve a single DV (outcome)
- UNI: correlation, t-test, ANOVA, ANCOVA
- MULTI: MANOVA, discriminant function analysis, multiple regression, logistic regression, canonical correlation, cluster analysis, factor analysis, MDS
classification not very strict
what is the general linear model (GLM)?
- an approach to assume and test a linear relationship between IVs (predictor) and DV. In GLM, the degrees to which
(1) a predictor is associated with DV, and
(2) a set of predictors as a set explains the variance in the DV (outcome), are examined. - straightforward to choose a statistical procedure suitable for a study with a clear research design, somewhat difficult cases are encountered when choosing between ANCOVA, Regression, Mixed-design ANOVA, and MANOVA
what is classified as the GLM Family?
DV
- Single (continuous, categorical)
- Multiple (continuous)
IV (and covariate)
- Categorical
- categorical and continuous
- continuous
ANOVA (single/categorical)
ANCOVA (single/categorical and continuous)
REGRESSION (single/continuous)
(not GLM but similar) LOGISTIC REGRESSION (single/categorical and continuous) DISCRIMINANT FUNCTION (single/continuous)
MANOVA (multiple/categorical)
MANCOVA (multiple/categorical and continuous)
what are the research objectives in quantitative data analysis?
- measure group means and compare between groups
- test casual models
- assess relationship among variables
- assess structure in and across complex relationships
what are the analytic methods in quantitative data analysis?
- t-test (35% Hons Thesis)
- ANVOVA (70% Hons Thesis)
- ANCOVA (70% Hons Thesis)
- MANOVA (70% Hons Thesis)
- Discriminant analysis
- correlation (50% Hons Thesis)
- reliability analysis (80% Hons Thesis)
- multiple regression (25% Hons Thesis)
- logistic regression (<5% Hons Thesis)
- path analysis (10% Hons Thesis)
- SEM (10% Hons Thesis)
- PCA and Factor analysis (10% Hons Thesis)
- cluster analysis, MDS
Multiple regression and logistic regression analysis
- Multi-causality
- Unique contributions of predictors (partial stats, ect)
- Interaction effects, too!
non-parametric = categorical
assumption: distribution of errors is normally distributed
what is the principal component analysis (PCA) and the exploratory factor analysis (EFA)
- PCA: how can we combine these variables into a smaller set of variables? explaining components (big list to represent happiness, want to reduce items)
- EFA: what is the underlying structure of these variables? how they relate to each other (levels of happiness, different factors and structure of measure) exploratory
Latent Factor 1
Latent Factor 2
what is confirmatory factor analysis (CFA)?
CFA starts with a theory to guide your analysis
used to confirm
• Distinctions are made between latent constructs that are error free, and their indices that involve error. (e.g., authoritarian parent {construct} and smacking {indices/error})
The analysis informs about an overall ‘fit’ of the model
what is a path analysis (mediation analysis)
Path Analysis examines the causal structure among the variables.
indirect effects
direct effects
what is the structural equation modelling (SEM)?
- combination of CFA and PA
- measurement model = CFA
- structural model = PA (causal)
- models fit is analysed
what is cluster analysis and multidimensional scaling (MDS)?
- clustering assigns variables, or cases, that are similar to one another in groups
- MDS is a method of visualising patterns of relationship among variables or cases based on similarities