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Summary Multivariate Data Analysis

ISBN-10 129202190X ISBN-13 9781292021904
289 Flashcards & Notes
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A snapshot of the summary - Multivariate Data Analysis ISBN: 9781292021904

  • 1 College Factor Analysis

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  • How is Factor analysis an Interdependence technique?
    Factor analysis is an Interdependence technique in that an entire set of interdependent relationships is examined without making the distinction between dependent and independent variable.
  • In what circumstances is factor analysis used?
    • To identify underlying demensions, or factors, that explain the correlations among a set of variables.
    • To indentify a new, smaller, set of uncorrelated variables to replace the origian set of correlated variables in subsequent multivariate analysis (E.G. Regression or ancova)
  • What are the two forms of factor analysis?
    Explaratory and confirmatory
  • What is meant with exploratory factor analysis?
    • Researcher intends to find an underlying structure
    • researcher has assumptions that superior factors cause correlations between variables
    • researcher intends to reveal interrelationships
    • generation of hypotheses
  • What is meant with confirmatory factor analysis?
    • Researcher has a priori ideas of the underlying factors that derive from theory
    • Researcher identifies relationships between variables and factors before conducting the factor analysis
    • Testing hypotheses
    • special case of structural equation models
  • What is meant with Data Matrix X
    Contains the characteristics of objects that derived from questioning prersons
  • What is meant with standard data matrix Z
    Z contains the standardized characteristics of objects (Standradized data always have a mean of 0 and a standard deviation of 1)
  • What is meant with rotated factor loadings A*?
    Contains correlations between factors and variables after rotation of the coordinate plane
  • What are the steps of conducting Factor analysis?
    1. Problem formulation
    2. construction of the correlation matrix
    3. selecting the method of factor analysis
    4. determination of number of factors
    5. rotation of factors
    6. interpretation of factors
      1. Calculation of factor scores
      2. or Selection of surrogate variables
      3. Creation of summated scores
    7. .
    8. Determination of Model Fit
  • What is meant with formulating the problem in factor analysis?
    • The objectives of factor analysis should be identified.
      • data summarization?
      • Data reduction
    • The variables to be included in the factor analysis should be specified based on past research, theory, and judgment of the researcher. It is important that the variables be appropriately measured on an interval or ratio scale.
    • An appropriate sample size should be used. As a rough guideline, there should be at least four or five times as many observations (Sample size) as there are variables

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