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

1
Q

What are the two major data analytic approaches in psychological research?

A
  • exploring relationships between variables

- comparing groups

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2
Q

what analyses are used to conduct statistical analyses to explore relationships?

A
  • 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)

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3
Q

what analyses are used to conduct statistical; analyses to compare groups?

A
  • t-tests
  • analysis of variance (ANOVA)
  • analysis of covariance (ANCOVA) / multivariate analysis of variance (MANOVA)
  • discriminant analysis
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4
Q

what is the difference between univariate statistics and multivariate statistics?

A
  • 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

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5
Q

what is the general linear model (GLM)?

A
  • 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
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6
Q

what is classified as the GLM Family?

A

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)

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7
Q

what are the research objectives in quantitative data analysis?

A
  • measure group means and compare between groups
  • test casual models
  • assess relationship among variables
  • assess structure in and across complex relationships
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8
Q

what are the analytic methods in quantitative data analysis?

A
  • 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
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9
Q

Multiple regression and logistic regression analysis

A
  • Multi-causality
  • Unique contributions of predictors (partial stats, ect)
  • Interaction effects, too!

non-parametric = categorical

assumption: distribution of errors is normally distributed

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10
Q

what is the principal component analysis (PCA) and the exploratory factor analysis (EFA)

A
  • 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

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11
Q

what is confirmatory factor analysis (CFA)?

A

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

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12
Q

what is a path analysis (mediation analysis)

A

Path Analysis examines the causal structure among the variables.

indirect effects
direct effects

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13
Q

what is the structural equation modelling (SEM)?

A
  • combination of CFA and PA
  • measurement model = CFA
  • structural model = PA (causal)
  • models fit is analysed
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14
Q

what is cluster analysis and multidimensional scaling (MDS)?

A
  • 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
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