Day 1: Introduction to multi-level data problems

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Long v. wide data format: PPMD example ◮ The PPMD dataset is organized as long data, where the basic unit of variation is the Score variable
Long v. wide data format: PPMD example ◮ The PPMD dataset is organized as long data, where the basic unit of variation is the Score variable ◮ Score represents the placement on a 1–20 point scale of either the left-right location or the low–high importance
Page 1 and 2: Day 1: Introduction to multi-level
Page 3 and 4: Course logistics and overview ◮ P
Page 5 and 6: Course logistics and overview ◮ P
Page 7 and 8: What is multilevel data? ◮ Multil
Page 15 and 16: The structure of multilevel data 5
Page 17 and 18: The structure of multilevel data 5
Page 19 and 20: Why would special models be needed
Page 21 and 22: The ecological fallacy ◮ The ecol
Page 23 and 24: The ecological fallacy ◮ The ecol
Page 25 and 26: The atomistic fallacy ◮ The atomi
Page 27 and 28: Stata and “robust” clustered st
Page 29 and 30: Stata and “robust” clustered st
Page 31 and 32: The organization of multilevel data
Page 33 and 34: The organization of multilevel data
Page 35 and 36: Zen and the art of reshapeing ◮ s
Page 37 and 38: Zen and the art of reshapeing ◮ s
Page 39 and 40: Zen and the art of reshapeing conti
Page 41 and 42: Benoit and Marsh (2008) example con
Page 43: Long v. wide data format: PPMD exam
Page 47 and 48: Long v. wide data format: PPMD exam
Page 49 and 50: Long v. wide data format: PPMD exam
Page 51 and 52: Reshape example with expert survey
Page 53 and 54: Reshape example with expert survey
Page 55 and 56: Introducing variance decomposition
Page 57 and 58: Introducing variance decomposition

Day 1: Introduction to multi-level data problems

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