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Table 3 Australia in 2016. Multiple linear regression model outputs of factors influencing daily milk yields in does on a large dairy goat enterprise in south western Victoria

From: The prevalence of Coxiella burnetii shedding in dairy goats at the time of parturition in an endemically infected enterprise and associated milk yield losses

Variable Coefficient (SE) t p value 95% CI
Intercept 2.38 (0.11) 21.26 < 0.001 2.15 to 2.59
qPCR status:
 Negative Reference   - -
 Positive low -0.08 (0.12) -0.68 0.495 -0.33 to 0.16
 Positive high -0.53 (0.23) -2.33 0.02 -0.98 to -0.08 a
Parity:
1 Reference   - -
 2 0.34 (0.10) 7.29 < 0.001 0.54 to 0.94
 3 1.22 (0.11) 10.7 < 0.001 0.99 to 1.44
 4+ 0.71 (0.13) 5.5 < 0.001 0.46 to 0.96
Kidding season:
 March to April Reference   - -
 June to July 0.06 (0.11) 0.49 0.62 -0.17 to 0.28
 September to October 0.53 (0.12) 4.52 < 0.001 0.3 to 0.77
 November to December 0.54 (0.12) 4.57 < 0.001 0.3 to 0.77
Farm:
 A Reference   - -
 B 0.24 (0.10) 2.34 0.02 0.04 to 0.44
 C -0.71 (0.11) -6.72 < 0.001 -0.92 to -0.5
Random effect SD    
 Goat id 0.82    
Within goat temporal correlation with first order autoregressive structure (AR1): 0.23
  1. AIC: 343081.1
  2. aInterpretation: After adjusting for the effect of parity, kidding season, days in milk and farm, daily milk yields from does that were qPCR-positive high were 530 (95% CI 80 to 980) mL less than does that were qPCR negative. The random effect at the goat level accounts for repeated measures and individual animal variability.
  3. SE: standard error.
  4. CI: confidence interval