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BUAN 6337 EXAM 2 FULLY SOLVED & UPDATED 2024 $15.49   Add to cart

Exam (elaborations)

BUAN 6337 EXAM 2 FULLY SOLVED & UPDATED 2024

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  • Course
  • BUAN-302
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  • BUAN-302

BUAN 6337 EXAM 2 FULLY SOLVED & UPDATED 2024

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  • August 2, 2024
  • 30
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • BUAN-302
  • BUAN-302
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BRAINBOOSTERS
BUAN 6337 EXAM 2 FULLY SOLVED & UPDATED 2024
Longitudinal Data Analysis:
- How data is measured
- The models can distinguish... - answer - Repeated measurements are taken on a subject through time
- The models can distinguish changes over time within subjects from differences between subjects at their baseline levels & study changes over time between groups
Longitudinal Data Analysis:
- The models can estimate __________________ level regression parameters and ____________________ level regression parameters. - answer individual-
level (subject specific); population-level
Examples of Longitudinal Studies (3): - answer - Examine how price, capacity, and utilization affect the cost of an individual airline
- Examine whether the return on education changed over time
- Examine productivity growth across firms over time
Models that assume the observations are independent (OLS Regression) might be inappropriate for longitudinal data because - - answer - Measurements taken on the same subject
tend to be more similar than measurements taken on different subjects
- Measurements taken close in time on the same subject tend to be more similar than measurements taken far apart in time
- The variances of longitudinal data often change with time
Proc Panel Characteristics: - Can handle...
- Can handle...
- Can produce...
- Can test... - answer - Can handle a variety of error structures
- Can handle unbalanced panels
- Can produce several HCCME and HAC covariance matrices
- Can test for poolability, panel stationarity, autocorrelation
Proc Panel Error Structures (3 bullets): - answer - Fixed-effects, random effects, and hybrid models (Hausman-T aylor, Amemiya-MaCurdy
- Autoregressive models (first-order autoregression,
dynamic model with lagged regressors)
- Moving average models
Model Building Strategies:
- Conduct...
- Fit...
- T est...
- Run...

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