Table S8: Results of the Negative Binomial Count Model of Breakdown Duration, With DVO Omitted From the Random Effects and Log Patch Prevalence Included in the Fixed Effects. Log Main Sett Is Included as a Fixed Effect (Untransformed Model Coefficients)

doi 10.7717/peerj.8319/supp-9

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Table 2: Parameter Estimates of the Fixed Effectexplanatory Variables in the Final Model for Both the Count Model (Negative Binomial) and Ordinal Model.

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Figure 5: Correlations Between (A) Mean Breakdown Length Per DVO and Main Sett Density and (B) Mean Patch-Level bTB Prevalence and Main Sett Density. (C) Shows the Relationship Between Main Sett and Breakdown Duration on a Per-Dvo Basis, Including Only Data Available for Each DVO, and (D) Is the Same as With (C), but Without Confidence Intervals and Predicted Against the Full Range of Values for All DVOs.

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7. Fixed-Effects Negative Binomial Regression Models

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Table S8: Results of the Negative Binomial Count Model of Breakdown Duration, With DVO Omitted From the Random Effects and Log Patch Prevalence Included in the Fixed Effects. Log Main Sett Is Included as a Fixed Effect (Untransformed Model Coefficients)

Full Text

Abstract

Date

Authors

Publisher

Related search

Table 2: Parameter Estimates of the Fixed Effectexplanatory Variables in the Final Model for Both the Count Model (Negative Binomial) and Ordinal Model.

7. Fixed-Effects Negative Binomial Regression Models

Technology Diffusion in Hospitals: A Log Odds Random Effects Regression Model

Table 2: Linear Mixed-Effects Model Coefficients and Associated S.E. Explaining Log- Transformed Seedling Biomass.

Table 1: Explanatory Variables Included in the Final Model.

Estimation of Random Coefficients Logit Demand Models With Interactive Fixed Effects

A General Panel Model With Random and Fixed Effects: A Structural Equations Approach

Discreteness of Log Discrepancies Over Log Canonical Triples on a Fixed Pair