report.ivreg.md
In report: Automated Reporting of Results and Statistical Models

report-survreg

Code
  report(ivr)
Message
  Formula contains log- or sqrt-terms.
    See help("standardize") for how such terms are standardized.
  Formula contains log- or sqrt-terms.
    See help("standardize") for how such terms are standardized.
Output
  We fitted a linear model to predict packs with rprice, rincome and salestax
  (formula: log(packs) ~ log(rprice) + log(rincome)). The model's explanatory
  power is substantial (R2 = 0.42, adj. R2 = 0.39). The model's intercept,
  corresponding to rprice = 0 and rincome = 0, is at 9.43 (95% CI [6.69, 12.17],
  t(45) = 6.94, p < .001). Within this model:

    - The effect of rprice [log] is statistically significant and negative (beta =
  -1.14, 95% CI [-1.87, -0.42], t(45) = -3.18, p = 0.003; Std. beta = -0.53, 95%
  CI [-0.86, -0.20])
    - The effect of rincome [log] is statistically non-significant and positive
  (beta = 0.21, 95% CI [-0.33, 0.76], t(45) = 0.80, p = 0.429; Std. beta = 0.12,
  95% CI [-0.14, 0.39])

  Standardized parameters were obtained by fitting the model on a standardized
  version of the dataset. 95% Confidence Intervals (CIs) and p-values were
  computed using a Wald t-distribution approximation.