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Advanced Statistical Analysis Using IBM SPSS Statistics (V19) (0G093G)

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Detailed Course Outline

Factor Analysis

  • Explain the basic theory of factor analysis and the steps in factor analysis
  • Explain the assumptions and requirements of factor analysis
  • Specify a factor analysis and interpret the output

K-Means Cluster Analysis

  • Explain the basic theory of cluster analysis and the steps in doing a cluster analysis
  • Explain the approach of K-Means cluster analysis
  • Specify a K-Means cluster analysis and interpret the output

TwoStep Cluster Analysis

  • Explain the basic approach of TwoStep cluster analysis
  • Specify a TwoStep cluster analysis
  • Use the Model Viewer to study and interpret the output

Binary Logistic Regression

  • Explain the basic theory and assumptions of logistic regression
  • Specify a logistic regression analysis
  • Interpret model fit, logistic regression coefficients and model accuracy

Multinomial Logistic Regression

  • Explain the basic theory of multinomial logistic regression
  • Specify a multinomial logistic regression analysis
  • Interpret model fit, logistic regression coefficients and model accuracy

Discriminant Analysis

  • Explain the basic theory of discriminant analysis and how cases are classified
  • Specify a two-group discriminant analysis and interpret the resulting output
  • Complete additional analysis and validation of the discriminant model

Nearest Neighbor Analysis

  • Explain the basic approach of nearest neighbor analysis
  • Explain the meaning of k in the analysis and how cases are classified
  • Specify a nearest neighbor analysis and interpret the resulting output in the Model Viewer

Kaplan-Meier Analysis

  • Explain the general principles of survival analysis
  • Specify a Kaplan-Meier analysis and interpret the resulting tabular and graphical output
  • Specify a Kaplan-Meier analysis with a strata variable, and with pairwise comparisons

Cox Regression

  • Explain the general principles of Cox regression
  • Specify a Cox regression analysis and interpret the resulting tabular and graphical output
  • Test the assumption of proportional hazards
  • Specify a Cox regression with time-varying covariate for variables that don’t meet the assumption of proportionality

Generalized Linear Models

  • Explain the use of the exponential family of distributions and a link function and how these differential a generalized linear model from a general linear model
  • Specify a Generalized Linear Model analysis and interpret the resulting output
  • Check model assumptions and predictions

Linear Mixed Models

  • Explain the general principles of a linear mixed model approach to data analysis
  • Specify a Linear Mixed Model analysis and interpret the resulting output, building successive models of greater complexity