Advanced Data

Created by LEC Team
Last updated Mon, 27-Mar-2023
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Course Objectives of Advanced Data

  • Estimation of basic models in R/ Python

  • Approaches to dealing with missing data.

  • Data reduction techniques

 



Day 1
Principal components analysis

  • Rescaling principal components

  • Choosing the number of components

  • Component scores 



Day 2
Factor analysis
  •  Factor extraction and common factor analysis

  •  Factor rotation and factor scores

Item response theory models

  • Latent trait models and item response function

  • Logistic and normal IRT models and interpreting the IRT score scale



Day 3
Structural equation modeling and path models

  • Path diagrams

  • Structural equations& designing SEMs•

  • Confirmatory factor analysis

  • Latent class models



Day 4
Clustering and cluster analysis, and association rules

  • Classification in social sciences

  • Hierarchical clustering; k-means clustering;

  • Model-based clustering

  • Visualization of clustering results



Day 5
Missing data

  • Missing data generation and mechanisms

  • Multiple imputations

  • Pattern mixture models

  • Data missing not at random

  • Missing data in longitudinal studies

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Dates Venues Price Details
2023-06-05 Paris $5750 Details
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2023-07-31 Paris $5750 Details
2023-08-28 Paris $5750 Details
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2023-06-05 Berlin $5750 Details
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2023-07-31 Berlin $5750 Details
2023-08-28 Berlin $5750 Details
2023-09-25 Berlin $5750 Details
2023-10-23 Berlin $5750 Details
2023-11-20 Berlin $5750 Details
2023-12-18 Berlin $5750 Details