Summary for a Monthglm — summary.monthglm • season

The default summary method for an object produced by monthglm().

Usage

# S3 method for class 'monthglm'
summary(object, ...)

Arguments

object: a monthglm object produced by nscosinor().
...: further arguments passed to or from other methods.

Value

a list with the following elements:

n: sample size.
month.ests: parameter estimates for the intercept and months.
month.effect: scale of the monthly effects. RR for rate ratios, OR for odds ratios, or empty otherwise.

Details

The estimates are the mean, 95\ p-value (comparing each month to the reference month). If Poisson regression was used then the estimates are shown as rate ratios. If logistic regression was used then the estimates are shown as odds ratios.

See also

monthglm, plot.monthglm

Author

Adrian Barnett a.barnett@qut.edu.au

Examples

mmodel <- monthglm(
  formula = cvd~1,
  data = CVD,
  family = poisson(),
  offsetpop = expression(pop/100000),
  offsetmonth = TRUE
  )
summary(mmodel)
#> Number of observations = 168 
#> Rate ratios
#>  
#>                mean     lower     upper     zvalue        pvalue
#> monthsFeb 0.9001334 0.8835557 0.9170223 -11.093389  1.350710e-28
#> monthsMar 0.8248895 0.8097153 0.8403480 -20.321628  8.278563e-92
#> monthsApr 0.7861180 0.7713300 0.8011895 -24.836563 3.612571e-136
#> monthsMay 0.7431550 0.7290823 0.7574993 -30.432988 2.011735e-203
#> monthsJun 0.7169580 0.7031100 0.7310788 -33.437125 3.960379e-245
#> monthsJul 0.7001582 0.6866705 0.7139109 -35.915811 1.730663e-282
#> monthsAug 0.7037277 0.6901913 0.7175297 -35.456352 2.315335e-275
#> monthsSep 0.7033356 0.6896741 0.7172678 -35.164379 7.008762e-271
#> monthsOct 0.7365838 0.7226003 0.7508379 -31.263630 1.457403e-214
#> monthsNov 0.7894712 0.7746378 0.8045886 -24.426747 8.891612e-132
#> monthsDec 0.9286091 0.9120533 0.9454655  -8.069682  7.048164e-16