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| Information Theory is a statistical ____ |
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| Akaike's Infromation Criteria |
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| type of analysis that evaluates hypotheses based on the least amount of information lost |
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| conclusions we draw from analysis (models) |
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Akaike
Information
Criterion |
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guy who developed it
Uses info, so LOSS of info is critical component of the analysis
should be criteria for multiple ways to infer from analysis |
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which model most support
ranking of models
probability of model
likelihood of model A vs. model B. |
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| Kullback-Leibler Information |
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| seek model that minimizes information lost between model g and reality. |
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| AIC used Kullback-Leibler information as a basis, but there is |
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| substantial uncertainty in this estimation |
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| Botlzmann's entropy and K-L information and maximum likelihood |
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| Link between null hypothesis testing and information theory___ |
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| RSS, or the information NOT explained by the treatment (why some stats tests can be used for null hyp. and inf. theory) |
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biologically based
estimable parameters
principle of parsimony (simplest model best) |
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| most of the models will non linear such as _______ |
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| be logit based (0,1) or (either/or) |
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1. a priori models
2. calculate AICc
3. Assess differences
4. Assess model likelihoods
5. Asses model probabilities (weights)
6. Calculate evidence ratios
7. Draw inference |
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| Use multiple selection criterion |
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| model likelihoods, AICc, change in AICc, evidence ratios |
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| Standard notation for regression coefficient |
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| model representing science hypothesis “i” |
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parameter vector (variances) |
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