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Model Assumptions.pdf

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Preview of Model Assumptions
🔗 Source: workshop.samplesizeshop.org
📊 Size: 228 KB
👤 Author: aritzhaupt
⬇️ Downloads: 139

Summary

Three common statistical models are used for multilevel and longitudinal studies:
1. Univariate linear model: applied to uncorrelated data with a single outcome measure.
2. Multivariate linear model: used for experiments with multiple outcomes or hypotheses.
3. Mixed linear model: a more flexible model making fewer assumptions than the multivariate model.

Key terms related to model assumptions include:
1. Correlation: measures the linear relationship between two variables, ranging from -1 to 1.
2. Residual: not defined in this section.
3. Variance: not defined in this section.

Correlation indicates the strength and direction of the relationship between two random variables, with:
- Positive correlation (0 to 1) indicating variables change in the same direction.
- Negative correlation (-1 to 0) indicating variables change in opposite directions.
- A correlation of 0 indicating unrelated variables.
- Variables with correlation equal to zero are considered independent for the purposes of this class.

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Description

1. Univariate linear model
2. Multivariate linear model
3. Mixed linear model.

Technical Information

  • File Format: PDF
  • File Size: 228 KB
  • Pages: 18
  • Language: EN
  • Author: aritzhaupt
  • Total Downloads: 139
  • Last Updated: 1 week ago

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